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“Z™ Important Exposure Factors for 
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f, MEADE An Analysis of Laboratory and 

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Observational Field Data 
Characterizing Cumulative 
Exposure to Pesticides 




EPA 600/R-07/013 



Important Exposure Factors 

for Children 

An Analysis of Laboratory and Observational 
Field Data Characterizing Cumulative 
Exposure to Pesticides 

By 

Peter P. Egeghy 1 , Linda S. Sheldon 1 , Roy C. Fortmann 1 , Daniel M. Stout II 1 , Nicolle S. Tulve 1 , Elaine Cohen 
Hubal 2 , Lisa J. Melnyk 3 , Marsha Morgan 1 , Paul A. Jones 1 , Donald A. Whitaker 1 , Carry W. Croghan 1 , April Coan 1 
^S EPA, Office of Research and Development, National Exposure Research Laboratory, Human Exposure and 

Atmospheric Sciences Division, Research Triangle Park, NC 27711 
2 US EPA, Office of Research and Development, National Center for Computational Toxicology, Research 

Triangle Park, NC 27711 

3 US EPA, Office of Research and Development, National Exposure Research Laboratory, Microbiological and 
Chemical Exposure Assessment Research Division, Cincinnati, OH 45268 


U.S. Environmental Protection Agency 
Office of Research and Development 
Washington, DC 20460 



Notice 



The U.S. Environmental Protection Agency, through its Office of Research and Development, funded and 
managed or partially funded and collaborated in the research described in this report. It has been subjected to the 
Agency’s peer and administrative review and has been approved for publication as an EPA document. Mention of 
trade names or commercial products does not constitute endorsement or recommendation for use. 


Wi'j W7 


LC Control Number 



2007 467168 


11 



Abstract 


In an effort to facilitate more realistic risk assessments that take into account unique childhood 
vulnerabilities to environmental toxicants, the U.S. EPA’s National Exposure Research 
Laboratory (NERL) developed a framework for systematically identifying and addressing the 
most important sources, routes, and pathways of children’s exposure to pesticides. Four priority 
research areas were identified as representing critical data gaps in our understanding of 
environmental risks to children. Several targeted studies were conducted under NERL’s 
children’s exposure research program to specifically address these priority research needs. This 
document is a comprehensive summary report of data collected in these studies to address the 
priority research needs and is intended for an audience of exposure scientists, exposure modelers, 
and risk assessors. The parameters measured and the measurement methods are described. Data 
on representative organophosphate and pyrethroid pesticides are compared across studies and 
across compounds with the primary purpose of identifying or evaluating important factors 
influencing exposures along each relevant pathway. Summary statistics, comparative analyses, 
and spatial and temporal patterns are presented to address previously identified data gaps. 

Results are compared across studies in order to identify trends that might provide a better 
understanding of the factors affecting children’s exposures. While highlights of the results of 
individual studies are presented, the focus is on presenting insights gleaned from the analysis of 
the aggregated data from several studies. By examining relationships among application 
patterns, exposures, and biomarkers for multiple compounds from different classes of pesticides, 
this report strives to help produce more reliable approaches for assessing cumulative exposure. 


m 





Executive Summary 


In an effort to facilitate more realistic risk assessments that take into account unique childhood 
vulnerabilities to environmental toxicants, the National Exposure Research Laboratory (NERL) 
in the U.S. Environmental Protection Agency’s (U.S. EPA) Office of Research and Development 
(ORD) developed a framework for systematically identifying and addressing the most important 
sources, routes, and pathways of children’s exposure to pesticides (Cohen Hubal et al., 2000a, 
2000b). Using this framework, a screening-level assessment was performed to identify the 
exposure pathways with the greatest potential exposures. The uncertainty associated with 
assessing exposure along each pathway was then evaluated through an exhaustive review of 
available data. Four priority research areas were identified as representing critical data gaps in 
our understanding of environmental risks to children. The absence of sufficient real-world data 
in all four of these areas produces an excessive reliance on default assumptions when assessing 
exposure. These priority research areas are: 1) pesticide use patterns; 2) spatial and temporal 
distributions of residues in residential dwellings; 3) dermal absorption and indirect (non-dietary) 
ingestion; and 4) dietary ingestion. 

Several targeted studies were conducted or financially supported by NERL under the children’s 
exposure research program to specifically address these priority research needs. These studies 
included: 

• Children’s Total Exposure to Persistent Pesticides and Other Persistent Organic 
Pollutants (“CTEPP”) 

• First National Environmental Health Survey of Child Care Centers (“CCC”) 

• Biological and Environmental Monitoring for Organophosphate and Pyrethroid Pesticide 
Exposures in Children Living in Jacksonville, Florida (“JAX”) 

• Center for the Health Assessment of Mothers and Children of Salinas Quantitative 
Exposure Assessment Study (“CHAMACOS”) 

• Children’s Pesticide Post-Application Exposure Study (“CPPAES”) 

• Distribution of Chlorpyrifos Following a Crack and Crevice Type Application in the US 
EPA Indoor Air Quality Test Research House (“Test House”) 

• Pilot Study Examining Translocation Pathways Following a Granular Application of 
Diazinon to Residential Lawns (“PET”) 

• Dietary Intake of Young Children (“DIYC”) 

• Characterizing Pesticide Residue Transfer Efficiencies (“Transfer”) 

• Food Transfer Studies (“Food”) 

• Feasibility of Macroactivity Approach to Assess Dermal Exposure (“Daycare”) 

Two studies performed prior to the identification of priority research areas also provided useful 
data. These were: 


v 



• National Human Exposure Assessment Survey in Arizona (NHEXAS-AZ) 

• Minnesota •Children’s Pesticide Exposure Study (“MNCPES”) 

All studies involving children were observational research studies, as defined in 40 CFR Part 
26.402. All study protocols and procedures to obtain the assent of the children and informed 
consent of their parents or guardians were reviewed and approved by an independent institutional 
review board (IRB) and complied with all applicable requirements of the Common Rule 
regarding additional protections for children. Further, all protocols regarding recruitment and 
treatment of participants were reviewed by the EPA Human Subjects Research Review Official 
(HSRRO) to assure compliance with the Federal Policy for the Protection of Human Subjects. 

The studies took place in EPA research laboratories, in the EPA Indoor Air Quality Research 
Test House, in private residences, and in child care centers. The studies have been grouped as 
a) large observational field studies (NHEXAS-AZ, MNCPES, CTEPP, and CCC), b) small pilot- 
scale observational studies (JAX, CPPAES, DIYC, CHAMACOS, and Daycare), and 
c) laboratory studies (Test House, Transfer, and Food). The large observational field studies had 
either a regional (NHEXAS-AZ, MNCPES, CTEPP) or national (CCC) focus. A broad suite of 
chemical contaminants, including organophosphate and pyrethroid pesticides and their metab¬ 
olites, were typically measured in multiple environmental media and in urine. Some of the small 
pilot-scale studies included measurements of multiple chemicals in multiple media in locations 
either with year-round residential pesticide use (JAX) or in close proximity to agricultural fields 
(CHAMACOS). Other pilot-scale studies focused on a single compound (CPPAES, DIYC, PET, 
Daycare). The laboratory studies (Transfer, Food, Test House) evaluated factors affecting 
transfer from surfaces or investigated post-application spatial and temporal variability. One of 
the primary objectives for all of these studies was to determine and quantify the key factors that 
influence exposure along the pathways relevant to the four priority research areas. 

This document is a comprehensive summary report of data collected under the NERL children's 
exposure research program and is intended for an audience of exposure scientists, exposure 
modelers, and risk assessors. The parameters measured and the measurement methods are 
described. Data on representative organophosphate and pyrethroid pesticides are compared 
across studies and across compounds with the primary purpose of identifying or evaluating 
important factors influencing exposures along each relevant pathway. Summary statistics, 
comparative analyses, and spatial and temporal patterns are presented to address previously 
identified data gaps. Results are compared across studies in order to identify trends that might 
provide a better understanding of the factors affecting children’s exposures. While highlights of 
the results of individual studies are presented, the focus is on presenting insights gleaned from 
the analysis of the aggregated data from several studies. By examining relationships among 
application patterns, exposures, and biomarkers for multiple compounds from different classes of 
pesticides, this report strives to help produce more reliable approaches for assessing cumulative 
exposure. 

With limited data available to EPA researchers on the types, locations, and frequency of 
pesticide usage in residential and other non-occupational environments, pesticide use patterns 
were identified as a priority research area . Accordingly, pesticide use information was collected 
by inventory and questionnaire in each of the field studies. Questionnaire items and inventory 


vi 



forms differed, geographic regions represented were limited, and the total number of study 
participants was relatively small. Furthermore, during the period of four years covered (1997 to 
2001), pesticide manufacturers were increasingly replacing organophosphates with pyrethroids in 
their formulations, and restrictions on residential applications of the most commonly used 
organophosphates were approaching. Nevertheless, important usage information was produced 
by the studies. Pyrethrins and their synthetic analogs (pyrethroids), specifically permethrin, 
cypermethrin, and allethrin, are clearly, the most frequently used insecticides for indoor appli¬ 
cations in homes and child care centers based on inventories and records. Organophosphates 
appear to persist in indoor environments, as chlorpyrifos and diazinon were more frequently 
detected in screening wipes (at frequencies comparable to permethrin) than in inventories. 

Among the carbamates, only propoxur and carbaryl were inventoried or reportedly used. 

“Crack-and-crevice” type applications were used more often than either broadcast or total release 
aerosol (“fogger”) applications. Applications were more likely to be performed by the resident 
than by a professional service in JAX, and also as reported in NHANES. In JAX, the modes of 
application included hand pump sprayer (37%), aerosol can (24%), fogger (3%), and baits (3%), 
but the pertinence of these results to other locations is unknown. Apart from these results, 
information on application type and method was not collected. 

Pesticide products were found in at least 86% of JAX and MNCPES screening households, with 
a mean of three products per household. There is evidence in support of a pattern of higher 
application frequencies in warmer climates, with the percentage of participants reporting use in a 
given time period highest in Florida, lower in North Carolina and Ohio, and lowest in Minnesota. 
The percentage in Jacksonville, FL is substantially higher, and the percentage in Minnesota is 
substantially lower, than the national average reported in NHANES. In childcare centers, 
monthly interior pesticide applications were performed in about a third of the CCC facilities 
nationwide and were anecdotally found to be standard practice among daycares contacted in 
North Carolina. 

There were no statistically significant differences in the total number of products found or 
reportedly used in MNCPES based on either population density (urban vs. non-urban 
households) or other socio-demographic factors including race, ethnicity, home type, income, 
and level of education. Similarly, analysis of CTEPP data found no association between 
application frequency and either population density or income class. 

A second primary research area is spatial and temporal distributions of pesticides in residential 
dwellings. Spatial and temporal heterogeneity may affect exposure estimates along all exposure 
routes. Absorption via the inhalation route relies on the measured airborne concentration. 
Absorption via the dermal and indirect ingestion routes relies on the measured surface loading. 
Even estimates of dietary ingestion for children may depend on surface concentrations due to 
pesticide transfer during food preparation and handling. Examination of distribution patterns of 
airborne and surface residues has yielded important insights. 

The organophosphate insecticides chlorpyrifos and diazinon were most frequently detected in 
both indoor air and outdoor air in these field studies, but the detection frequencies in outdoor air 
were lower and more variable across studies. Chlorpyrifos was frequently detected even after its 


Vll 



indoor residential use was restricted, perhaps due to emissions from indoor sinks ( e.g ., carpets) 
and from continued use of existing home inventories. Indoor air concentrations were typically 
an order of magnitude higher than outdoor air concentrations, with notable exceptions of outdoor 
diazinon and permethrin levels which were nearly as high as indoor levels in JAX, and outdoor 
diazinon levels that exceeded indoor levels in the agricultural community monitored in 
CHAMACOS. The low pesticide concentrations routinely measured outdoors (notwithstanding 
the exceptions noted) together with the relatively short time spent outdoors suggests that 
inhalation of outdoor air is not typically an important contributor to aggregate pesticide 
exposure. The similarity across large observational field studies in the variability of the 
observed indoor air chlorpyrifos concentrations, despite sample collection periods ranging from 
1 to 7 days, suggests that air concentrations are reasonably consistent from day-to-day in the 
absence of a recent application. 

The median indoor air concentrations of the organophosphates are higher than that of the 
pyrethroids. While these studies were conducted at a time when organophosphates arguably 
dominated the marketplace, a comparison of the mean levels of various organochlorine, 
organophosphate, and pyrethroid pesticides measured in CTEPP finds that the concentrations 
measured in the absence of recent applications appear to be strongly influenced by vapor 
pressure, with the more volatile pesticides, such as chlorpyrifos, found at the highest levels. 
Consequently, the importance of inhalation as a route of exposure for pesticides is likely to 
decrease as less volatile pesticides, such as the pyrethroids, are introduced into the market. 

Differences in sampling methods, year of the study, and time of year when samples were 
collected make it difficult to distinguish any regional differences in pesticide concentrations. In 
general, median indoor air concentrations were somewhat higher in southern states (NHEXAS- 
AZ and CTEPP-NC) than in northern states (MNCPES and CTEPP-OH). However, the 
distributions exhibit considerable overlap across geographical locations. When daycare 
measurements are included, a geographical difference is less obvious, perhaps due to regular, 
calendar-based pesticide treatments at many daycare facilities. 

Irrespective of region, differences in indoor air levels between homes and daycares were not 
found to be statistically significant. Similar mean indoor air levels observed in homes and 
daycares demonstrate the potential for continued exposure as a child spends time in other indoor 
locations. Additional concentration measurements in other locations would be useful to examine 
exposure potential from different settings such as schools, restaurants, and other public and 
private locations where pesticides are also applied. 

Differences in indoor air concentrations associated with population density and income level 
were observed in the field studies. Differences between urban and rural air concentrations were 
observed in both MNCPES and CTEPP. In fact, urban chlorpyrifos levels were about 25% 
higher than rural levels across studies. A reasonable explanation may be that urban areas require 
more intensive use of pesticide products to control a range of pests over a wider seasonal span. 
Concentrations of chlorpyrifos and diazinon were higher in low-income homes than in 
medium/high income homes in CTEPP, but the difference was statistically significant only for 
diazinon, and only in NC. 


Vlll 


Within-home spatial and temporal patterns were investigated following a crack and crevice 
application of chlorpyrifos in the kitchen of the Test House. The pesticide was detected even in 
the farthest bedroom from the application, with a concentration gradient observed from the 
kitchen to the den (proximal area) to the master bedroom (distal area). Temporally, airborne 
concentrations peaked on day 1, then decreased by approximately 80%, but were still 
measurable, at 21 days after application. In contrast, airborne diazinon concentrations among 
homes in the DIYC study were most pronounced 4-5 days after application. Between-home 
spatial variability following a pesticide application was investigated in the CPPAES study. 
Indoor air chlorpyrifos concentrations spanned more than an order of magnitude among the 
homes one day after application. 

Significant progress has also been made in understanding spatial and temporal distributions of 
organophosphate residues on surfaces. In a published analysis of the MNCPES surface wipe 
data, Lioy and colleagues (2000) reported substantial variability in surface chlorpyrifos levels 
among different rooms. Substantial variability among and within rooms is also evident in the 
Daycare data. Furthermore, data from the Test House also show that surface loadings cannot be 
assumed to be homogenous even within a room. These observations suggest that multiple 
locations should be sampled to more accurately represent surface loadings. Exposure modelers 
using probabilistic methods have already begun to account for differences in surface loadings 
based on proximity to application sites in order to reduce possible exposure misclassification in 
their exposure estimates. 

A number of observations suggest that there is substantial translocation of pesticides from 
application surfaces to adjacent surfaces, but levels remain higher at the application location. In 
CPPAES, the post-application chlorpyrifos loadings were higher than the pre-application values 
even on surfaces that did not receive a direct application. In DIYC, the transferable residues on 
the counters were nearly as high as those on the floors immediately after application. In JAX, 
the application area surface residue loadings were generally higher than the play area surface 
residue concentrations. In the CCC, the floor residue loadings were generally higher than the 
desk top loadings. High loadings of diazinon in indoor house dust following the lawn treatment 
in the PET study suggest that transfer into the house may also occur. 

Examination of chlorpyrifos and diazinon loadings following applications indicates that total 
available residue loadings decay at a slower rate than airborne concentrations. Total available 
residue loadings (obtained by methods intended to measure the total amount of contaminant on a 
surface) also appear to decline at a slower rate than transferable residue loadings (intended to 
represent the amount that is transferred as a result of contact with the contaminated surface). In 
fact, using a total available residue method, chlorpyrifos was measured in 62% of the MNCPES 
samples, even in the absence of a recent pesticide application. 

On a regional level, Jacksonville, Florida, an area known for year-round pest control issues and 
identified as having high pesticide usage during the NOPES study (Whitmore et al., 1994), had 
much higher surface concentrations than any of the other studies without recent applications. 
Within a given region, however, there appears to be little relationship between questionnaire 
information and measured surface values. Previously published results from the MNCPES 
indicate that the residential pesticide use questions and overall screening approach used in the 
MNCPES were ineffective for identifying households with higher levels of individual target 


IX 


pesticides (Sexton et al., 2003). Results from the CPPAES study suggest that cleaning activities 
and ventilation influence surface concentrations; it appears that the surface chlorpynfos loadings 
were lower in those homes in which the occupants reported additional cleaning activities and/or 
high ventilation rates. 

While significant progress has been made in understanding spatial distributions of organo- 
phosphate and pyrethroid pesticides in the absence of a recent application and in understanding 
spatial and temporal distributions of organophosphate pesticides following an application, no 
data have been produced on the spatial and temporal distributions of pyrethroids following 
applications. The movement of residentially applied insecticides follows a complex and poorly 
understood process of transformation and phase distribution and is influenced by several factors. 
Differences in physicochemical characteristics make it difficult to generalize the spatial and 
temporal distributions of organophosphate pesticides to pyrethroid pesticides, but with 
information on chemical properties and on human activities, distribution patterns can be 
modeled. 

The third primary research area was identified as dermal absorption and indirect ingestion. 

Intake via these exposure routes is often estimated using measurements of pesticide 
concentrations in dust and soil and pesticide loadings on surfaces. Intake estimates also rely on 
numerous default exposure factor assumptions. Pesticides in dust generally had high detection 
frequencies, consistent with dust being considered a repository of contaminants. Detection 
frequencies for soil samples, on the other hand, were generally low (with the exception of 
measurements made immediately following lawn applications). 

Compounds found at relatively higher concentrations in dust tend to be found at relatively lower 
concentrations in air. The less volatile pyrethroid pesticides tend to partition to the dust and may 
degrade more slowly allowing accumulation over time from repeated applications. This 
underscores the importance of dust as a primary residential exposure medium for the less volatile 
pesticides. In addition, the exposure factors that are important for other nonvolatile 
contaminants such as lead may also be important for the less volatile pesticides. 

Pyrethroids generally have low vapor pressures and Henry’s Law constants, thus they are poorly 
volatilized and exist almost entirely in the particulate phase at room temperature. Furthermore, 
high octanol/water (Ko W ) and water/organic carbon (Ko C ) partition coefficients cause pyrethroids 
to partition into lipids and into organic matter. With these characteristics, pyrethroids can be 
expected to bind readily to the particulate matter that comprises house dust. Particles 
resuspended by human activity then act as the primary vector for pyrethroid transport and for 
human exposure. Particle-bound movement and transfer of pyrethroids imply a decreased 
importance of the inhalation route and an increased importance of routes that involve dermal 
transfer, such as indirect ingestion and dermal absorption. Exposure of young children, for 
whom indirect ingestion of residues from object- and hand-to-mouth activities is particularly 
important, may be most strongly affected. In fact, algorithm-based estimates of distributions of 
intake of chlorpyrifos and permethrin from the four contributing routes among the CTEPP-OH 
children indicated that the contribution from the indirect route is much more important for 
permethrin than for chlorpyrifos. 


x 



Comparisons of pesticide surface loadings (ng/cm 2 ) showed higher levels in the CTEPP daycare 
centers than in the homes. This appears to be the result of higher amounts of dust in the daycare 
centers, as there is not as large of a difference in the pesticide concentrations (ng/g) in the dust. 
Studies with lead have suggested that loading may have a greater impact than concentration on 
actual intake, thus higher amounts of dust may be important even if the concentration within the 
dust is similar. 

Data from our studies show that the collection methods utilized may have sizeable effects on 
estimates of dermal exposure and indirect ingestion. Total residue methods, which use both 
solvent and mechanical action to remove residues that may have penetrated into the surface, 
produce the highest values, followed by dust methods, and then by transferable residue methods. 
These methods are intended to measures different types of transfer, and efficiencies for various 
methods have been previously published. Use of total residue methods allows the assessor to use 
appropriate transfer factors to represent a transfer efficiency applicable to a given scenario. 
Questions remain, however, on exactly how much of what is measured by total residue methods 
is truly available for transfer and how much would otherwise be trapped in the pores and/or body 
material of the surfaces if not for the mechanical and solvent action of the methods. 

Even the amount of solvent used with wipe samples affects the results. The low pesticide 
surface loadings obtained with 2 mL isopropyl alcohol wipes in both the NC and OH CTEPP 
studies (loadings similar to those obtained with the polyurethane foam [PUF] roller) suggest that 
the amount of IP A applied to the wipe may affect the amount of pesticide residue recovered. 
Surface type has also been shown to affect the collection efficiency of wipes. Recently 
published NERL data (Rohrer et al., 2003) found that with respect to pesticide transfer, wiping 
from hard surfaces greatly exceeded carpet, and wiping from tile generally exceeded hardwood. 
Clearly, some standardization of surface sampling methods is needed. 

Although successfully used in laboratory studies, the Modified Cl8 Surface Press Sampler was 
rarely able to measure pesticide residues in field studies. The original press sampler was 
designed to measure transfer of dust-bound pesticides to the skin from a single hand press onto a 
carpeted surface. The uses for the modified Cl8 surface press sampler have expanded to include 
hard surfaces and longer contact times, effectively using the press sampler in a manner for which 
it was not intended. Our data suggest that the sensitivity of the modified Cl 8 surface press 
sampler may be too low to measure residential pesticide residues (which may transfer by both 
equilibrium mass transfer and mechanical transfer). 

Laboratory studies using fluorescent tracers (as surrogates for pesticide residues) indicated that 
tracer type , surface type , contact motion , and skin condition were all significant factors. 

Transfer was greater with laminate (over carpet), smudge (over press), and sticky skin (over 
moist or dry). Contact duration and pressure (force) were not found to be important factors. 

The effect of surface type appeared to diminish with repeated contact, while the effect of skin 
condition (moist vs. dry) appeared to increase with repeated contact. Additional studies are still 
needed to gain a better understanding of the key factors that influence the dermal transfer and 
indirect ingestion of pesticides. 


xi 


The frequencies of hand- and object-to-mouth contacts were quantified for preschool children in 
the CTEPP and CPPEAS studies using the Virtual Timing Device (VTD) software (Zartarian et 
al.. 1997). The CPPAES results support the use of the commonly assumed median count of 9.5 
hand-to-mouth contacts per hour; however CTEPP data suggest a much higher value for younger 
children. The CTEPP methodology also accounts for combination hand- and object-to-mouth 
contacts during both eating and non-eating events. 

The fourth primary research area was identified as dietary ingestion. Diet can be an important 
pathway of exposure. Foods may contain residues of pesticides and other environmental 
chemicals because of intentional applications or may become contaminated during processing, 
distribution, storage, and consumption. For certain chemicals, diet is potentially the predominant 
pathway of exposure. Children’s dietary exposure to pesticides is not limited to the residues in 
or on foods when they are brought into the home. Children’s unique handling of foods prior to 
consumption requires special attention, but it is rarely considered in study designs. 

Based on route-specific intake estimates, dietary ingestion represented the dominant route of 
exposure for chlorpyrifos, diazinon, and permethrin in the CTEPP study. Unfortunately, the 
route that represented the dominant route of exposure was also the route with the lowest 
detection frequencies (approximately 2/3 of the values for permethrin in CTEPP were 
nondetects), which increases the uncertainty in the estimates. Substituting a fraction of the 
detection limit for values below the limit of detection may have a disproportionate impact on 
assessing the importance of the dietary route. 

The most common measure of dietary exposure was by composited duplicate diet analyses. 
However, great care must be taken to ensure that the duplicate diet accurately reflects what is 
actually consumed instead of what is served because significant quantities of food may remain 
uneaten by children. Duplicate diets fail to capture those pesticide residues transferred to foods 
as a result of the child’s handling of food prior to and during consumption. In DIYC, estimates 
of dietary intake that included excess contamination due to handling were as much as double the 
estimates of intake based on duplicate diet alone. These results suggest that dietary estimates 
based on duplicate diet may not be as reliable for young children as they are for adults. 

Progress has been made in many areas and we are beginning to understand the environment that 
children live in, their activities, and the resulting exposures. However, research is still needed to 
adequately characterize the magnitude, routes and pathways of exposure. We still need to 
understand the key factors that influence the dermal transfer and indirect ingestion of pesticides. 
We need to be able to more accurately assess dietary exposure. In order to evaluate exposure 
models, we must be able to quantify the relationships between and among environmental 
concentrations of pesticides in various media, children’s activities, and the results of biomarkers 
of exposures as measured in urine and/or blood. Exposure models outputs that include the 
timing and route of exposure need to be linked to PBPK models in order to develop accurate 
assessment of target tissue dose. Research, especially model development, needs to extend 
beyond single chemical aggregate exposures and dose to include exposures and risks that 
accumulate across chemicals and over time. 


Xll 



Table of Contents 


Abstract .iii 

Executive Summary . v 

Tables .xvi 

Figures .xx 

Acknowledgments . xxiii 

Abbreviations and Acronyms .xxiv 

1.0 INTRODUCTION...1 

1.1 Background.,.1 

1.2 Purpose of the Report and Intended Audience.2 

1.3 Structure of the Report.4 

1.4 Data Treatment.5 

1.5 Description of the Studies and Data Collected.5 

1.6 Pesticides of Interest to this Report. 7 

1.7 Summary Descriptions of the Studies.9 

1.8 Exposure and Dose Models. 12 

2.0 PESTICIDE USE PATTERNS..13 

2.1 Sources of Information. 13 

2.2 Application Frequency.17 

2.3 Application Locations. 19 

2.4 Application Types and Methods.20 

2.5 Pesticides Identified in Inventories, Records and Wipe Samples.20 

2.6 Demographic Factors Influencing Applications.21 

3.0 AIR CONCENTRATION MEASUREMENTS. 25 

3.1 Introduction and Data Availability.25 

3.2 Pesticide Presence. 25 

3.3 Comparisons of Air Concentrations.30 

3.4 Differences Related to Location.:.37 

3.5 Spatial and Temporal Variability.41 

3.6 Factors that Influence Air Concentrations.41 

3.7 Summary: Air Concentrations.43 

4.0 SURFACE MEASUREMENTS.47 

4.1 Introduction and Data Availability.47 

4.2 Dust and Soil Measurements.50 

4.3 Total Available Residue Measurements. 59 

4.4 Transferable Residue Measurements.66 

4.5 Spatial and Temporal Variability. 73 

4.6 Differences Related to Location.77 

4.7 Influential Factors.78 


xm 








































4.8 Correlations among Soil, Wipes, and Dust.79 

4.9 Particle-Bound Pyrethroid Residues: Implications toward Exposure.80 

5.0 DIETARY EXPOSURE MEASUREMENTS.81 

5.1 Introduction and Data Availability.81 

5.2 Pesticide Presence.83 

5.3 Relative Importance of the Ingestion Route.90 

6.0 INDIRECT INGESTION MEASUREMENTS.93 

6.1 Characterizing Hand- and Object-to-Mouth Activities.93 

6.2 Residue Loadings on Mouthed Objects and Removal by Mouthing.94 

6.3 Transfer of Pesticide Residues to Food.98 

6.4 Indirect Ingestion of Dust and Soil.103 

6.5 Indirect Ingestion: Summary.104 

7.0 DERMAL EXPOSURE MEASUREMENTS.105 

7.1 Laboratory Fluorescent Measurement Studies.106 

7.2 Measurements of Pesticides on Hands by Wipe and Rinse Methods.112 

7.3 Measurements with Cotton Garments.123 

8.0 URINARY BIOMARKER MEASUREMENTS.129 

8.1 Toxicokinetics of Organophosphate and Pyrethroid Pesticides.129 

8.2 Measurements of Pesticide Metabolites in Urine.133 

8.3 Temporal Variability in Biomarker Measurements.141 

8.4 Urine and Creatinine Excretion among Children.144 

8.5 Relative Importance of Exposure Routes.146 

8.6 Model Predictions.152 

9.0 SUMMARY AND CONCLUSIONS.153 

10.0 REFERENCES.155 

11.0 BIBLIOGRAPHY.162 

APPENDIX A: Summary Statistics.165 

Air Concentrations.166 

Dust and Soil Concentrations and Loadings.170 

Total Available Surface Residue Loadings.176 

Transferable Surface Residue Loadings.179 

Solid Food Concentrations and Intakes. 1 82 

Hand Loadings. 186 

Urinary Metabolite Concentrations.188 

APPENDIX B: Individual Study Details.189 

National Human Exposure Assessment Survey in Arizona (NHEXAS-AZ).190 

Minnesota Children’s Pesticide Exposure Study (MNCPES). 191 

Children’s Total Exposure to Persistent Pesticides and Other Persistent Organic Pollutants 

Study (CTEPP). 192 

First National Environmental Health Survey of Child Care Centers (CCC).193 

Biological and Environmental Monitoring for Organophosphate and Pyrethroid Pesticide 

Exposures in Children Living in Jacksonville, Florida (JAX). 194 

Center for the Health Assessment of Mothers and Children of Salinas Quantitative Exposure 

Assessment Study (CHAMACOS). 195 

Children’s Pesticide Post-Application Exposure Study (CPPAES). 196 


xiv 












































The Distribution of Chlorpyrifos Following a Crack and Crevice Type Application in the US 

EPA Indoor Air Quality Research Test House (Test House).197 

A Pilot Study Examining Translocation Pathways Following a Granular Application of 

Diazinon to Residential Lawns (PET).198 

Dietary Intake of Young Children (DIYC).199 

Characterizing Pesticide Residue Transfer Efficiencies (Transfer).200 

Feasibility of Macroactivity Approach to Assess Dermal Exposure (Daycare).201 

Food Transfer Studies, also known as Press Evaluation Studies (Food).202 


xv 








Tables 


Table 1.1 Available media, participant characteristics, and activities by study. 8 

Table 1.2 Pesticides and metabolites measured in the studies. 8 

Table 2.1 Pesticides use information collection methods.16 

Table 2.2 Proportion (unweighted) of participants reporting pesticide use by study.18 

Table 2.3 The proportion of CTEPP participants reporting use of four types of pesticides.18 

Table 2.4 Pesticides inventoried in 36 households in Jacksonville, FL (JAX) in fall 2001.22 

Table 2.5 Most commonly applied pyrethroids in 1217 households with complete 12 month 

REJV survey data, as reported by Ozkaynak (2005).22 

Table 2.6 Number of pesticide products applied during one year (2001) in 168 child care centers 

(CCC), as reported by the center directors and/or professional applicators.23 

Table 2.7 Pesticides inventoried and used in 308 households in Minnesota (MNCPES) in 

summer 1997 (adapted from Adgate et al., 2000).. 23 

Table 2.8 Detection frequencies of target analytes in soil and wipe samples in the CCC study 

(weighted) and in screening wipe samples collected in JAX (unweighted).24 

Table 3.1 Summary of air sample collection methods. 27 

Table 3.2 Limits of detection (ng/m 3 ) for air samples by compound and study.28 

Table 3.3 Median and 95 th percentile air concentrations (ng/m 3 , unweighted) for frequently 

detected pesticides.31 

Table 3.4 Spearman correlations among personal, indoor, and outdoor concentrations of 

chlorpyrifos and diazinon measured in MNCPES. 39 

Table 3.5 Urban and rural differences in airborne concentrations of chlorpyrifos and diazinon 

measured in MNCPES. 39 

Table 3.6 Differences in airborne concentrations measured in CTEPP for urban versus rural, low 

versus medium income, and home versus daycare expressed as ratios of geometric means. 39 

Table 3.7 Airborne chlorpyrifos residues collected following a crack and crevice type application 

versus a total release aerosol in the EPA Test House. 44 

Table 4.1 Studies and sample collection methods for surface measurements.48 

Table 4.2 Limits of detection (ng/g or ng/cm 2 ) for surface measurements by study, method, and 

compound. 49 

Table 4.3 Median and 95 th percentile values for soil (ng/g) and dust (ng/cm 2 and ng/g) 

measurements by study.. 

Table 4.4 Median and 95 th percentile values for total available residues (ng/cm 2 ) by study.63 

Table 4.5 Median and 95 th percentile values for transferable residues (ng/cm 2 ) by study.70 

Table 5.1 Dietary exposure sample collection methods for pesticides.82 

Table 5.2 Limits of detection (pig/kg) for pesticides measured in duplicate diets.84 


iL 1 ... U I 

Table 5.3 Median and 95 percentile pesticide concentrations (pg/kg) measured in duplicate diet 

food samples... 

Table 6.1 Collection methods for the transfer of pesticide surface residues to food or objects. 95 


xvi 



























Table 6.2 Videotaped children’s hand- and object-to-mouth activity details.96 

Table 6.3 Videotaped hand-to-mouth and object-to-mouth counts.96 

Table 6.4 Objects commonly mouthed by preschoolers in CTEPP.96 

Table 6.5 Median and 95 th percentile pesticide loadings (ng/cm 2 ) measured on toy surfaces.97 

Table 6.6 The transfer efficiency (percent transfer, mean ± sd) of pesticide residues from treated 
surfaces to foods (relative to transfer to IPA wipes), after a 10-min contact duration (Food 

Transfer Studies)...99 

Table 6.7 The transfer efficiency (percent transfer, mean ± sd) of pesticide residues from a 

treated ceramic tile surface to various foods and to an IPA Wipe (Food Transfer Studies).100 

Table 6.8 The measured and predicted ingestion (ng/day) of diazinon from the DIYC.101 

Table 6.9 The estimated exposures (ng/day) of NC and OH preschool children in the CTEPP 

study to chlorpyrifos, diazinon, and permethrin through indirect ingestion.103 

Table 7.1 Factors commonly believed to affect dermal transfer.107 

Table 7.2 Study parameters tested in surface-to-skin transfer experiments in the Characterizing 

Pesticide Residue Transfer Efficiencies study.107 

Table 7.3 Skin loadings (mean, standard deviation) measured following surface-to-skin transfer 

experiments (initial experiments). 108 

Table 7.4 Statistical analysis results (p-values) from initial surface-to-hand transfer experiments 

(Riboflavin). 109 

Table 7.5 Statistical analysis results (p-values) from refined, follow-up surface-to-hand transfer 

experiments (Riboflavin and Uvitex).109 

Table 7.6 Evidence of importance of factors tested across surface-to-skin transfer experiments. 


.110 

Table 7.7 Limits of detection (ng/cm 2 ) for dermal measurements by compound and study.114 

Table 7.8 Median and 95 th percentile values of pesticide hand loadings (ng/cm 2 ) measured by 

hand rinse (HR) or hand wipe (HW) in the large observational field studies.114 

Table 7.9 Comparison of chlorpyrifos and diazinon loadings (ng/cm 2 ) on children’s hands 

measured with hand rinse (HR) and hand wipe (HW) methods.115 

Table 7.10 Pesticide loading (ng/cm 2 ) on cotton garments worn by children in three studies... 125 
Table 7.11 Results of multiple linear regression modeling of measured bodysuit pesticide loading 

(ng/cm 2 /sec) from data collected in the daycare study.126 

Table 7.12 Estimates of between- and within-person variability for loading on individual 

bodysuit sections. 126 

Table 8.1 Absorption and elimination characteristics for pesticides and urinary biomarkers of 

pesticide exposure.132 

Table 8.2 Summary of the children’s urinary biomarker collection methods.135 

Table 8.3 Urinary metabolites of organophosphate and pyrethroid pesticides measured in the 

children’s observational measurement studies.136 

Table 8.4 Limits of detection (ng/mL) for each pesticide metabolite measured in the children’s 

urine samples by study.136 

Table 8.5 Median and 95 th percentile values (ng/mL) for the pesticide metabolites TCPy, IMP, 

and 3-PBA measured in the children’s urine samples by study.. 136 

Table 8.6 Intraclass correlation coefficients (ICC) for logged CTEPP urinary metabolites.142 

Table 8.7 Between- and within-person geometric standard deviations (GSDs) for logged urinary 
concentrations from children in the CTEPP study. 142 


XVII 



























Table 8.8 Estimated relative importance of the inhalation, dietary ingestion, and indirect 

ingestion routes of exposure among children in CTEPP NC and OH.147 

Table A.l Summary statistics for airborne chlorpyrifos concentrations (ng/m 3 ) by study.166 

Table A.2 Summary statistics for airborne diazinon concentrations (ng/m 3 ) by study.167 

Table A.3 Summary statistics for airborne malathion concentrations (ng/m 3 ) by study.167 

Table A.4 Summary statistics for airborne ds-permethrin concentrations (ng/m 3 ) by study.168 

Table A.5 Summary statistics for airborne £ra«s-permethrin concentrations (ng/m 3 ) by study. 168 

Table A .6 Summary statistics for airborne TCPy concentrations (ng/m 3 ) by study.169 

Table A.7 Summary statistics for airborne IMP concentrations (ng/m 3 ) by study.169 

Table A .8 Summary statistics for chlorpyrifos concentrations measured in soil (ng/g).170 

Table A.9 Summary statistics for chlorpyrifos measured in dust, presented as both loading 

(ng/cm 2 ) and concentration (ng/g).170 

Table A. 10 Summary statistics for diazinon concentrations measured in soil (ng/g).171 

Table A.l 1 Summary statistics for diazinon measured in dust, presented as both loading (ng/cm 2 ) 

and concentration (ng/g).171 

Table A. 12 Summary statistics for ds-permethrin concentrations measured in soil (ng/g).172 

Table A. 13 Summary statistics for ds-permethrin measured in dust, presented as both loading 

(ng/cm 2 ) and concentration (ng/g).172 

Table A. 14 Summary statistics for fratts-permethrin concentrations measured in soil (ng/g)... 173 
Table A. 15 Summary statistics for rram'-permethrin measured in dust, presented as both loading 

(ng/cm 2 ) and concentration (ng/g).173 

Table A. 16 Summary statistics for cyfluthrin concentrations measured in soil (ng/g).174 

Table A. 17 Summary statistics for cyfluthrin measured in dust, presented as both loading 

(ng/cm 2 ) and concentration (ng/g).174 

Table A. 18 Summary statistics for TCPy concentrations measured in soil (ng/g).175 

Table A. 19 Summary statistics for IMP concentrations measured in soil (ng/g).175 

Table A.20 Summary statistics for chlorpyrifos in Total Available Residue (ng/cm 2 ).176 

Table A.21 Summary statistics for diazinon in Total Available Residue (ng/cm 2 ).177 

Table A.22 Summary statistics for cis-permethrin in Total Available Residue (ng/cm 2 ).177 

Table A.23 Summary statistics for trans-permethrin in Total Available Residue (ng/cm 2 ).178 

Table A.24 Summary statistics for cyfluthrin in Total Available Residue (ng/cm 2 ).178 

Table A.25 Summary statistics for chlorpyrifos in Transferable Residue (ng/cm 2 ).179 

Table A.26 Summary statistics for diazinon in Transferable Residue (ng/cm 2 ).180 

Table A.27 Summary statistics for ds-permethrin in Transferable Residue (ng/cm 2 ).180 

Table A.28 Summary statistics for trans-permethrin in Transferable Residue (ng/cm 2 ).181 

Table A.29 Summary statistics for cyfluthrin using in Transferable Residue (ng/cm 2 ).181 

Table A.30 Summary statistics for chlorpyrifos measured in solid food, presented as both intake 

(fx g/day) and concentration (/-ig/kg). 32 

Table A.31 Summary statistics for diazinon measured in solid food, presented as both intake 

([X g/day) and concentration (fxg/kg) .:. 133 

Table A.32 Summary statistics for ds-permethrin measured in solid food, presented as both 

intake (/xg/day) and concentration (/-tg/kg).... 

Table A.33 Summary statistics for fraHs-permethrin measured in solid food, presented as both 

intake (j^g/day) and concentration (fx g/kg).. 

Table A.34 Summary statistics for TCPy measured in solid food, presented as both intake 
(fx g/day) and concentration (/ xg/kg ).. 


xvm 



































Table A.3 5 Summary statistics for IMP measured in solid food, presented as both intake (/zg/day) 

and concentration (/zg/kg).185 

Table A.36 Summary statistics for chlorpyrifos hand loadings (ng/cm 2 ).186 ' 

Table A.37 Summary statistics for diazinon hand loadings (ng/cm 2 ).186 

Table A.38 Summary statistics for cw-permethrin hand loadings (ng/cm 2 ). 186 

Table A.39 Summary statistics for /rarcs-permethrin hand loadings (ng/cm 2 ).187 

Table A.40 Summary statistics for TCPy hand loadings (ng/cm 2 ).187 

Table A.41 Summary statistics for IMP hand loadings (ng/cm 2 ).187 

Table A.42 Summary statistics for TCPy measured in urine (ng/mL).188 

Table A.43 Summary statistics for 3-PBA measured in urine (ng/mL).188 

Table A.44 Summary statistics for IMP measured in urine (ng/mL). 188 


xix 












Figures 


Figure 1.1 Modeling framework for children’s pesticide exposure from Cohen Hubal et al. 

(2000b).3 

Figure 2.1 Weighted percentage of child care centers reporting treatment of various rooms in the 

Child Care Centers (CCC) study.19 

Figure 3.1 Frequency of detection of pesticides measured in indoor and outdoor air in selected 

studies.29 

Figure 3.2 Log probability plots for chlorpyrifos, diazinon, and c/s-permethrin measured in large 

observational field studies.32 

Figure 3.3 Log probability plots for /ra«.s-permethrin, TCPy, and IMP measured in large 

observational field studies.33 

Figure 3.4 Indoor and outdoor air concentrations of chlorpyrifos, diazinon, and c/s-permethrin 

measured in selected studies.34 

Figure 3.5 Indoor and outdoor air concentrations of /ra«s-permethrin and TCPy measured in 

selected studies.35 

Figure 3.6 Log-scale relationships between levels of parent pesticide (ng/m 3 ) and degradate 

(ng/m 3 ) measured in CTEPP.36 

Figure 3.7 The detection frequencies of select pesticides and their metabolites measured from the 

indoor air (A) and outdoor air (B) of homes and daycares in NC and OH.40 

Figure 3.8 Airborne concentrations (ng/m 3 ) of chlorpyrifos or diazinon measured from indoor air 

over time in the Test House, PET, CPPAES, and DIYC studies.45 

Figure 3.9 Association between measured air concentration (ng/m 3 ) and Applied Effective 

Volume (ng/m 3 /h) on the second day after application of chlorpyrifos in CPPAES homes.46 

Figure 3.10 Pesticide air concentrations as a function of vapor pressure in CTEPP homes (A) and 

daycares (B).46 

Figure 4.1 Detection frequencies of pesticides and degradates in soil... 53 

Figure 4.2 Detection frequencies of pesticides and degradates in dust. 53 

Figure 4.3 Lognormal probability plots of soil concentrations (ng/g) for chlorpyrifos, diazinon, 

c/s-permethrin, JraHs-permethrin, cyfluthrin, and TCPy. 54 

Figure 4.4 Lognormal probability plots of dust concentrations (ng/g) and loadings (ng/cm 2 ) for 

chlorpyrifos, diazinon, and c/s-permethrin. 55 

Figure 4.5 Lognormal probability plots of dust concentrations (ng/g) and loadings (ng/cm 2 ) for 

/rarcs-permethrin, cyfluthrin, and TCPy.56 

Figure 4.6 Box-and-whisker plots of dust concentrations (ng/g) and loadings (ng/cm 2 ) for 

chlorpyrifos, diazinon, and m-permethrin. 57 

Figure 4.7 Box-and-whisker plots of dust concentrations (ng/g) and loadings (ng/cm 2 ) for trans- 

permethrin, cyfluthrin, and TCPy.. 

Figure 4.8 Detection frequencies for pesticides using total available residue collection methods. 
.62 


xx 






















Figure 4.9 Lognormal probability plots for the most frequently detected pesticides which include 

chlorpyrifos, diazinon, cis- and ^raMs-permethrin, cyfluthrin, and cypermethrin.64 

Figure 4.10 Box-and-whisker plots of total available residue surface loadings (ng/cm 2 ) for 

chlorpyrifos, diazinon, c/s-permethrin, /ra/w-permethrin, cypermethrin, and esfenvalerate.65 

Figure 4.11 Detection frequencies for pesticides using transferable residue collection methods. 68 
Figure 4.12 Lognormal probability plots for transferable residue loadings for the most frequently 
detected pesticides which include chlorpyrifos, diazinon, and cis- and trans- permethrin from 

CTEPP.71 

Figure 4.13 Box-and-whisker plots for transferable residue loadings for the most frequently 
detected pesticides which include chlorpyrifos, diazinon, cis- and ^rarcs-permethrin, cyfluthrin, 

and TCPy.72 

Figure 4.14 Total available surface residue loadings measured in multiple rooms over time in the 
Test House, in multiple rooms in ten homes in CPPAES, and on multiple surfaces in three homes 

in DIYC. 75 

Figure 4.15 Transferable residue measurements over time following an application from multiple 
locations in multiple rooms of the Test House and multiple surfaces in three homes in DIYC... 75 

Figure 4.16 Total available residue measurements from the Daycare study...76 

Figure 4.17 Spatial variability in deposition coupon loadings in the kitchen (application site) and 

den (adjoining room) of Test House following pesticide application.76 

Figure 5.1 The detection frequency of pesticides measured in duplicate diet food samples.85 

Figure 5.2 Lognormal probability plots of solid food concentrations (pg/kg) and intakes (pg/day) 

for chlorpyrifos, diazinon, and as-permethrin from large observational field studies.86 

Figure 5.3 Lognormal probability plots of solid food concentrations (pg/kg) and intakes (pg/day) 

for trans- permethrin, TCPy, and IMP from large observational field studies.87 

Figure 5.4 Box-and-whisker plots of solid food concentrations (pg/kg) and intakes (pg/day) for 

chlorpyrifos, diazinon, and c/s-permethrin across all studies...88 

Figure 5.5 Box-and-whisker plots of solid food concentrations (pg/kg) and intakes (pg/day) for 

fra/w-permethrin, TCPy, and IMP across all studies.89 

Figure 5.6 Comparison of SHEDS model prediction for dietary intake of czs-permethrin 

(pg/kg/day) and CTEPP measurement data.90 

Figure 5.7 Estimated mean proportion of aggregate potential exposure for CTEPP-NC children 

by exposure route.91 

Figure 5.8 Estimated mean proportion of aggregated potential exposure for CTEPP-OH children 

by exposure route.92 

Figure 6.1 Comparison of the median hand-to-mouth and object-to-mouth contacts per hour 

among CPPAES and MNCPES children.97 

Figure 6.2 Comparison of measured and predicted ingestion of diazinon (ng/day) from the 

DIYC.102 

Figure 7.1 Comparison of transfer efficiencies of fluorescent tracers and pesticides from laminate 

and carpet surfaces to various sampling media.110 

Figure 7.2 Hand loading by contact number, from the refined, follow-up experiments using 

Riboflavin (left panels) or Uvitex (right panels).Ill 

Figure 7.3 Log probability plots of hand loadings (MNCPES data are hand rinses, all others are 

hand wipes).116 

Figure 7.4 Comparison of hand loadings across studies.117 


xxi 























Figure 7.5 Ratios of hand wipe loading to floor wipe loading (left panel) and hand wipe loading 

to dust loading (right panel) for pesticides in CTEPP.1 ^ 

Figure 7.6 Relationship between children’s hand loadings measured at CTEPP homes and 

daycares.119 

Figure 7.7 Relationship between hand loadings among children and adults in CTEPP.120 

Figure 7.8 Relationship between hand wipe measurements and floor wipe measurements in 

CTEPP... 121 

Figure 7.9 Relationship between hand wipe measurements and floor dust measurements in 
CTEPP...122 


Figure 7.10 Bodysuit section loadings (ng/cm 2 ) by monitoring period from the Daycare study 127 
Figure 7.11 Relative standard deviations of esfenvalerate loadings on cotton garment sections 

among infants and preschoolers in the Daycare study.128 

Figure 7.12 Handwipe loadings (ng/cm 2 ) above method detection limit among infants and 

preschoolers in the Daycare study.128 

Figure 8.1 Detection frequencies of pesticide metabolites in the children’s urines samples by 

study.137 

Figure 8.2 Log probability plots of urinary TCPy, 3-PBA, and IMP concentrations across large 

observational field studies. NHANES results are included for comparison.138 

Figure 8.3 Box-and-whisker plots comparing the urinary TCPy and 3-PBA concentrations across 

studies.139 

Figure 8.4 Urinary TCPy concentrations (ng/mL) over time for the children in the high and low 

application groups in CPPAES.140 

Figure 8.5 Time profiles for chlorpyrifos in environmental media and TCPy concentrations in 

urine for all children in the CPPAES.140 

Figure 8.6 Concentration versus time plots for urinary TCPy measurements among CTEPP-NC 

and CTEPP-OH participants reporting a recent pesticide application.143 

Figure 8.7 Time-concentration profile for urinary IMP measurements among child and adult PET 

study participants following an outdoor granular turf pesticide application.143 

Figure 8.8 Estimates of age-specific urinary output and creatinine excretion, based on data from 


the MNCPES 


145 


Figure 8.9 The median estimated intakes of chlorpyrifos and TCPy in CTEPP-NC compared with 

the excreted median amounts of TCPy in the preschool children’s urine.147 

Figure 8.10 Intake of environmental TCPy through the dietary route correlated poorly (r 2 =0.01) 

with the amount of TCPy excreted in the urine of CTEPP-NC preschool children.148 

Figure 8.11 Estimated distributions of aggregate intake (“AGGR”) of chlorpyrifos and 

permethrin (ng/kg/day) and estimated distributions of the four contributing routes.148 

Figure 8.12 The contributions of inhalation, dermal absorption, diet, and nondietary ingestion to 

aggregate intake of c/s-permethrin. 149 

Figure 8.13 Children’s estimated aggregate intake of chlorpyrifos and permethrin compared to 

their measured urinary metabolites (CTEPP). 149 

Figure 8.14 Distributions of TCPy in urine across studies (bottom right panel) in comparison to 

distributions of chlorpyrifos in indoor air, outdoor air, dust, and soil across studies.150 

Figure 8.15 Distributions of TCPy in urine across studies (bottom right panel) in comparison to 

distributions of chlorpyrifos on surfaces, in solid food, and on hands across studies.151 

Figure 8.16 Comparison of TCPy in urine between SHEDS model and observed MNCPES data 
when TCPy in the environment is not considered (Source: Xue et al., 2004). 152 


XXII 

























Acknowledgments 


We would like to acknowledge the many researchers and support staff who contributed to this 
report by their design and implementation of the included studies. The contributors are too 
numerous to acknowledge individually, but the organizations that collaborated on this research 
are listed in the report and Appendix B. This report would not be possible without all of the hard 
work that was put into the individual studies. A number of other researchers in the Human 
Exposure and Atmospheric Sciences Division, including Dr. Jianping (Jim) Xue, Mr. Thomas 
McCurdy, Dr. Rogelio Tomero-Velez, and Mr. M. Scott Clifton, made valuable contributions to 
this report by their analyses of data, reviews, and comments. 

We would like to acknowledge the EPA Program Office scientists, NERL researchers, and 
Science to Achieve Results (STAR) program grantees who gathered at the NERL Workshop on 
the Analysis of Children’s Measurements Data (Tulve et al ., 2006) in September 2005 to assess 
the suitability of the data for testing key hypotheses and to suggest additional analyses. 

The authors also gratefully acknowledge the time, effort, and constructive comments offered by 
the peer reviewers, Dr. Laura Geer (Johns Hopkins University), Dr. Miles Okino (EPA), Dr. B.J. 
George (EPA), and Dr. Valerie Zartarian (EPA). The comprehensive review and comments by 
Mr. Kent Thomas (Associate Director for Human Health in the Human Exposure and 
Atmospheric Sciences Division) also contributed significantly to the quality of the final 
document. 

We would especially like to thank all of the study participants who worked so generously with 
the researchers to help make these observational studies a success. 


xxm 


Abbreviations and Acronyms 


%Det 

2,4-D 

3-PBA 

ACH 

AER 

AEV 

ANOVA 

ASTM 

ATSDR 

AZ 

Cl8 Press 

ccc 

CDC 

CDIM 

CHA 

CHAMACOS 


cis -P 

c-Perm 

c-Permethrin 

CPPAES Pre 

CPPAES 

CRE 

CTEPP 

CTEPP-NC 
CTEPP-NC d 
CTEPP-NC DAYCARE 
CTEPP-NC h 
CTEPP-NC HOME 
CTEPP-OH 
CTEPP-OH d 
CTEPP-OH DAYCARE 
CTEPP-OH h 
CTEPP-OH HOME 
DAP 


Percent of samples above detection limit 
2,4-Dichlorophenoxyacetic acid 
3-Phenoxybenzoic acid 
Air exchanges per hour 
Air exchange rate 
Application effective volume 
Analysis of variance 

American Society for Testing and Materials 
Agency for Toxic Substances and Disease Registry 
National Human Exposure Assessment Survey in Arizona 
Cl8 surface press sampler 

First National Environmental Health Survey of Child Care 
Centers Study 
Centers for Disease Control 
Children’s Dietary Intake Model 

Center for the Health Assessment of Mothers and Children 
of Salinas Quantitative Exposure Assessment Study 
Center for the Health Assessment of Mothers and Children 
of Salinas Quantitative Exposure Assessment Study 
c/s-Permethrin 
c/s-Permethrin 
c/s-Permethrin 

CPPAES Study, pre-application days only 
Children’s Pesticide Post-Application Exposure Study 
Creatinine 

Children’s Total Exposure to Persistent Pesticides and 
Other Persistent Organic Pollutants Study 
CTEPP Study, North Carolina homes and daycares 
CTEPP Study, North Carolina daycares only 
CTEPP Study, North Carolina daycares only 
CTEPP Study, North Carolina homes only 
CTEPP Study, North Carolina homes only 
CTEPP Study, Ohio homes and daycares 
CTEPP Study, Ohio daycares only 
CTEPP Study, Ohio daycares only 
CTEPP Study, Ohio homes only 
CTEPP Study, Ohio homes only 
Dialkylphosphate 


xxiv 


Daycare / DAYCARE 


Dep Coup 
DC 

DCHD 

DEET 

DIYC 

EOSHI 


Food 

FQPA 

GC/ECD 

GC/MS 

GLM 

GM 

GSD 

HUD 

HVS3 

ICC 

IMP / IMPy 
IPA 

IPA Wipe 
JAX 


JAX-AG 

JAX-AGG 

JAXAGGREGATE 

JAX-SC 

JAX-SCR 

JAXSCREENING 

LOD 

LWW 

Max 

MCPA 

MDA 

MDL 

MGK 264 

Min 

MNCPES / MN 

MPA 

N 

NC Daycare 
NC DC 
NC HM 
NC Home 


Feasibility of Macroactivity Approach to Assess Dermal 
Exposure Study 
Deposition coupon 
Deposition coupon 
Duval County Health Department 
N,N-diethyl-meta-toluamide 
Dietary Intake of Young Children Study 
Environmental and Occupational Health Sciences Institute 
Study 

Food Transfer Studies 

Food Quality Protection Act 

Gas Chromatography/Electron Capture Detector 

Gas Chromatography/Mass Spectroscopy 

Generalized linear model 

Geometric mean 

Standard deviation of the geometric mean 
US Department of Housing and Urban Development 
High Volume Small Surface Sampler 
Intraclass Correlation Coefficient 
2-Isopropyl-6-methyl-4-pyrimidinol 
Isopropyl alcohol 
Isopropyl alcohol wipe 
Biological and Environmental Monitoring for 
Organophosphate and Pyrethroid Pesticide Exposures in 
Children Living in Jacksonville, Florida Study 
JAX Study, Aggregate Exposure Assessment phase 
JAX Study, Aggregate Exposure Assessment phase 
JAX Study, Aggregate Exposure Assessment phase 
JAX Study, Screening phase 
JAX Study, Screening phase 
JAX Study, Screening phase 
Limit of detection 

Lioy-Weisel-Wainman wipe sampler 
Maximum 

(4-chloro-2-methylphenoxy)acetic acid 
Malathion dicarboxylic acid 
Minimum detection limit 
N-octyl bicycloheptene dicarboximide 
Minimum 

Minnesota Children’s Pesticide Exposure Study 
2-methyl-3-phenylbenzoic acid 
Sample size 

CTEPP Study, North Carolina daycares only 
CTEPP Study, North Carolina daycares only 
CTEPP Study, North Carolina homes only 
CTEPP Study, North Carolina homes only 


xxv 


NC 

NERL 

NHANES 

NHEXAS-AZ 

NOPES 

NRMRL 

OCHP 

OH Daycare 

OH DC 

OH HM 

OH Home 

OH 

OP 

OPP 

OPPT 

ORD 

P25 

P50 

P75 

P95 

PBPK 

PET 


PUF 

PYR 

REJV 

RTI 

SD 

SHEDS 

STAR 

TCPY / TCP / TCPy 
TE 

TEST / TESTHOUSE / Test House 


TESTHOUSE Pre 

/-Permethrin 

?-Perm 

trans -P 

Transfer 

US CPSC 

US EPA 

VTD 


North Carolina 

National Exposure Research Laboratory 

National Health and Nutrition Examination Survey Study 

National Human Exposure Assessment Survey in Arizona 

Non-Occupational Pesticide Exposure Study 

National Risk Management Research Laboratory 

Office of Children’s Health Protection 

CTEPP Study, Ohio daycares only 

CTEPP Study, Ohio daycares only 

CTEPP Study, Ohio homes only 

CTEPP Study, Ohio homes only 

CTEPP Study, Ohio 

Organophosphate 

Office of Pesticide Programs 

Office of Pollution Prevention and Toxics 

Office of Research and Development 

25 th percentile 

Median / 50 th percentile 

75 th percentile 

95 th percentile 

Physiologically-Based Pharmacokinetic Model 
A Pilot Study Examining Translocation Pathways 
Following a Granular Application of Diazinon to 
Residential Lawns Study 
Polyurethane foam 
Pyrethroid 

Residential Exposure Joint Venture 

Research Triangle Institute 

Standard deviation of the arithmetic mean 

Stochastic Human Exposure and Dose Simulation Model 

Science to Achieve Results 

3,5,6-Trichloro-2-pyridinol 

Transfer Efficiency 

The Distribution of Chlorpyrifos Following a Crack and 
Crevice Type Application in the US EPA Indoor Air 
Quality (IAQ) Research House Study 
Test House Study, pre-application day only 
frYms-Permethrin 
fraws-Permethrin 
^rajzs-Permethrin 

Characterizing Pesticide Residue Transfer Efficiencies 
US Consumer Product Safety Commission 
U.S. Environmental Protection Agency 
Virtual Timing Device 


xxvi 


1.0 INTRODUCTION 


1.1 Background 

The U.S. Environmental Protection Agency (U.S. EPA) has pledged to increase its efforts to 
provide a safe and healthy environment for children by ensuring that all EPA regulations, 
standards, policies, and risk assessments take into account special childhood vulnerabilities to 
environmental toxicants. Children are behaviorally and physiologically different from adults. 
Their interaction with their environment, through activities such as playing on floors, and 
mouthing of hands and objects, and handling of food, may increase contact with contaminated 
surfaces. Proportionately higher breathing rates, relative surface area, and food intake 
requirements may increase exposure. Differences in absorption, metabolism, storage, and 
excretion may result in higher biologically effective doses to target tissues. Immature organ 
systems may be more susceptible to toxicological challenges. Windows of vulnerability, when 
specific toxicants may permanently alter the function of an organ system, are thought to exist at 
various stages of development. 

Children are exposed to a wide variety of chemicals in their homes, schools, daycare centers, and 
other environments that they occupy. The chemicals to which they are exposed may originate 
from outdoor sources, such as ambient air contaminants, indoor sources such as building 
materials and furnishings, and from consumer products used indoors. One category of consumer 
products to which children may be exposed is pesticides that are used to control roaches, rats, 
termites, ants, and other vermin. Despite widespread residential and agricultural use of 
pesticides, only limited measurement data are available for pesticide levels in environments that 
children occupy and little is known about the factors that impact children’s exposures to 
pesticides. The Food Quality Protection Act (FQPA) of 1996 requires EPA to upgrade the risk 
assessment procedures for setting pesticide residue tolerances in food by considering the 
potential susceptibility of infants and children to both aggregate and cumulative exposures to 
pesticides. Aggregate exposures include exposures from all sources, routes, and pathways for 
individual pesticides. Cumulative exposures include aggregate exposures to multiple pesticides 
with the same mode of action for toxicity. FQPA requires risk assessments to be based on 
exposure data that are of high quality and high quantity or on exposure models using factors that 
are based on existing, reliable data. 

EPA’s Office of Research and Development (ORD) is responsible for conducting research to 
provide the scientific foundation for risk assessment and risk management at EPA. In 2000, 

ORD released its Strategy for Research on Environmental Risks to Children addressing research 
needs and priorities associated with children’s exposure to environmental pollutants and 
providing a framework for a core program of research in hazard identification, dose-response 
evaluation, exposure assessment, and risk management. 

The National Exposure Research Laboratory (NERL) in ORD is working to achieve three 
specific objectives of the Strategy through its children’s exposure research program: (1) develop 
improved exposure assessment methods and models for children using existing information; 

(2) design and conduct research on age-related differences in exposure, effects, and dose- 

response relationships to facilitate more accurate risk assessments for children; and (3) explore 


1 


opportunities for reducing risks to children. After an exhaustive review of the volume and 
quality of the data upon which default assumptions for exposure factors are based (Cohen Hubal 
et al., 2000a), a framework for systematically identifying the important sources, routes, and 
pathways for children’s exposure was developed (Cohen Hubal et al., 2000b). 

This framework (Figure 1.1), based on a conceptual model for aggregate exposure, provides the 
foundation for a protocol for measuring aggregate exposures to pesticides (Berry et al., 2001) 
and for developing sophisticated stochastic models (Zartarian et al., 2000). Using the 
framework, four priority research areas, representing critical data gaps in our understanding of 
environmental risks to children, have been identified: 

(1) Pesticide use patterns; 

(2) Spatial and temporal distribution in residential dwellings; 

(3) Dermal absorption and indirect (non-dietary) ingestion (including micro- and 
macro-activity approaches); and 

(4) Direct ingestion. 

Several targeted studies were designed and conducted to address these research needs. These 
include laboratory studies, small pilot field studies, and large collaborative observational studies. 
These studies aimed to: (1) evaluate methods and protocols for measuring children’s exposure, 
(2) collect data on exposure factors to reduce the uncertainty in exposure estimates and risk 
assessments, and (3) collect data for use in exposure model development and evaluation. 

1.2 Purpose of the Report and Intended Audience 

This document is a comprehensive summary report of data collected under or otherwise related 
to the NERL children's exposure research program. Data are compared across studies and across 
compounds to identify or evaluate important factors influencing exposures along each relevant 
pathway. Summary statistics, comparative analyses, and spatial and temporal patterns are 
presented to address previously identified data gaps. The primary purpose of this document is to 
identify factors that are most important for children's exposures to pesticides. The objectives of 
this document are to: 

• Compare results across studies in order to identify trends or similar observations that 
might provide a better understanding of the factors affecting children’s exposures; 

• Describe recent children’s exposure studies conducted or funded by NERL, including 
descriptions of the parameters measured and the measurement methods; 

• Provide concentration data and summary statistics for comparison of the studies; and 

• Present highlights of the results of the studies. 

The document was completed with input from staff in the EPA Program Offices, NERL 
researchers, and Science to Achieve Results (STAR) program grantees who gathered at the US 
EPA National Exposure Research Laboratory’s Workshop on the Analysis of Children’s 
Measurement Data (Tulve et al., 2006) in September 2005 to discuss data presented in a draft 
summary report, assess the suitability of the data for testing key hypotheses, and propose 
additional analyses. 


2 


Source 

o indoor 
residential 
o outdoor 
residential 
o industrial 
o agricultural 




Release 

& 

Transfer 


Inhalation 


Outdoor 


o 

air 

o 

water 

Q 

soil 

O 

plants 

o 

surfaces 

I 

▼ ( 

Indoor 

o 

air 

o 

water 

o 

house dust 

o 

food 

o 

surfaces 

o 

clothes 






Ingestion 


Dietary Ingestion 


Exposure 


\ Ingestion / ^ 


Rate 

^-\ Rate / 




Diet 


-Exposure- 


Figure 1.1 Modeling framework for children’s pesticide exposure from Cohen Hubal et al. 
(2000b). 


3 







































































The document is intended for an audience of exposure scientists, exposure modelers, and risk 
assessors. Exposure scientists will find a useful evaluation of available sampling methods for all 
media relevant to children’s exposures. Exposure modelers will be able to use the data to 
develop or improve probabilistic multimedia, multi-pathway human exposure models. Most 
significantly, the report may be used by EPA Program offices such as the Office of Pesticide 
Programs (OPP), the Office of Pollution Prevention and Toxics (OPPT), and the Office of 
Children’s Health Protection (OCHP) to enhance the Agency’s risk assessment activities by 
replacing default assumptions with high-quality, real-world data. Fewer default assumptions will 
lead to more accurate assessments of exposure and risk and will bolster ensuing risk reducing 
actions. Furthermore, by examining relationships among application patterns, exposures, and 
biomarkers for multiple compounds from different classes of pesticides, this report contributes to 
the development of more reliable approaches for assessing cumulative exposure. Some of the 
analyses and comparisons that are presented in this summary report include the following: 

• Comparison of concentrations 

• Spatial variability 

• Temporal variability 

• Regional comparisons 

• Urban versus rural 

• Home versus daycare 

• Indoor versus outdoor 

• Parent compound versus metabolite 

• Effect of physical and chemical properties 

• Impact of air exchange rate 

• Effect of surface type 

• Effect of surface concentration 

• Effect of sampling method 

Comparisons between studies may involve different numbers of measurements, different 
sampling strategies and methods, and different chemical analysis methods 

1.3 Structure of the Report 

This document presents data from studies to evaluate children’s exposure to pesticides, spanning 
from pesticide use patterns, through concentrations in exposure media, to biological markers of 
exposure. The exposure media are listed in an order that roughly mirrors the complexity of the 
exposure mechanism; that is, beginning with inhalation exposure and ending with dermal 
exposure. At the beginning of each section, available data from the relevant studies are listed. 
Results are presented in tables and graphs to illustrate the available data and to facilitate 
comparisons both across studies and across pesticides. 

Throughout the document, lognormal probability plots (“logplots”) and box-and-whisker plots 
(“box plots”) are used to graphically depict and compare distributions of concentrations or 
surface loadings. The logplots are used to compare results only from large observational field 
studies and the boxplots are used to compare results from the focused studies against each other 
and against the large observational field studies. In the lognormal probability plot, the ordered 


4 



values of the measured concentration are plotted on a log-scale vertical axis, and the percentiles 
of the theoretical normal distribution are plotted on the horizontal axis. If the points in the plot 
form a nearly straight line, the data are approximately lognormal. The box-and-whisker plot is 
actually a group of side-by-side box-and-whisker plots along the x-axis, each representing a 
different study. The upper whisker extends to the maximum value, the upper edge of the box 
represents the 75 th percentile, the line inside the box represents the median (50 th percentile), the 
lower edge of the box represents the 25 th percentile, and the lower whisker extends to the 
minimum value. Note that the vertical axis is log-scale. 

1.4 Data Treatment 

Values that are below the method detection limit (MDL) are common in environmental data sets. 
All values above the MDL are statistically different from zero; however, values near the MDL 
are generally less accurate than those much higher than the MDL. Laboratories often report a 
second limit, the Method Quantitation Limit (MQL), as the smallest amount that can be reliably 
quantified in a sample. Despite the higher relative uncertainty in values between the MDL and 
the MQL, all values above the MDL are retained for the purposes of this document. Values 
below the MDL are treated using simple substitution, wherein they are replaced with a fraction 
of the detection limit (MDL//2), a common practice originally proposed by Homung and Reed 
(1990). These substituted values are used in all statistical analyses performed specifically for 
this report and are presented in all data plots, except for lognormal probability plots, in which 
these substituted values were judged by the authors to be misleading. Detection frequencies (that 
is, the percent of measurements above the MDL) are presented for each compound by each 
relevant sampling method at the beginning of each chapter. 

Sampling weights are available for all of the large-scale observational field studies, but, unless 
otherwise noted, only unweighted concentrations are presented in this report. Summary statistics 
based on unweighted observations may not provide as valid an estimate of true study population 
values as those based on weighted observations, but are used nonetheless to maintain consistency 
in comparisons with studies for which weights are not available. In all cases where a statistical 
test was done to assess differences, the name of the test and the resulting p-value are presented. 

1.5 Description of the Studies and Data Collected 

Data are included in this report from the following studies. (The acronyms in parentheses are 
used in the Tables and Figures of this report.) 

• National Human Exposure Assessment Survey in Arizona (NHEXAS-AZ) 

• Minnesota Children’s Pesticide Exposure Study (“MNCPES”) 

• Children’s Total Exposure to Persistent Pesticides and Other Persistent Organic 
Pollutants (“CTEPP”) 

• First National Environmental Health Survey of Child Care Centers (“CCC”) 

• Biological and Environmental Monitoring for Organophosphate and Pyrethroid Pesticide 
Exposures in Children Living in Jacksonville, Florida (“JAX”) 

• Center for the Health Assessment of Mothers and Children of Salinas Quantitative 
Exposure Assessment Study (“CHAMACOS”) 


5 


• Children’s Pesticide Post-Application Exposure Study (“CPPAES”) 

• Distribution of Chlorpyrifos Following a Crack and Crevice Type Application in the US 
EPA Indoor Air Quality Research Test House (“Test House”) 

• Pilot Study Examining Translocation Pathways Following a Granular Application of 
Diazinon to Residential Lawns (“PET”) 

• Dietary Intake of Young Children (“DIYC”) 

• Characterizing Pesticide Residue Transfer Efficiencies (“Transfer”) 

• Food Transfer Studies (“Food”) 

• Feasibility of Macroactivity Approach to Assess Dermal Exposure (“Daycare”) 

All studies involving children were observational research studies, as defined in 40 CFR Part 
26.402. All study protocols and procedures to obtain the assent of the children and informed 
consent of their parents or guardians were reviewed and approved by independent Institutional 
Review Boards (IRBs) and complied with all applicable requirements of the Common Rule (45 
CFR 46) regarding additional protections for children (Subpart D). Further, all protocols 
regarding recruitment and treatment of participants were reviewed by the EPA Human Subjects 
Research Review Official (HSRRO) to assure compliance with the Federal Policy for the 
Protection of Human Subjects. 

The studies discussed in the report included large observational studies, such as NHEXAS-AZ, 
MNCPES, CTEPP, and CCC, small pilot-scale observational studies ( e.g ., JAX, CPPAES, 

DIYC, CHAMACOS, and Daycare), and laboratory studies (e.g., Test House, Transfer, and 
Food). 

• MNCPES, NHEXAS-AZ, CTEPP, and CCC were large observational exposure 
measurement studies with survey designs that involved random sampling. The CCC 
study was a nationwide survey and the others had a regional focus. Sampling weights are 
available for all of these studies, but, unless noted otherwise, only unweighted 
concentrations are presented in this report. 

• The small pilot-scale observational studies are small-scale field studies, such as JAX and 
CHAMACOS, which were performed to evaluate methods for conducting aggregate 
exposure assessments for pesticides and to collect preliminary data that could be used to 
assist in the design of larger observational studies. Like the large observational studies, 
some of these smaller studies included measurements of multiple chemicals in multiple 
media. 

• The laboratory studies consisted of experiments under controlled conditions to evaluate 
factors affecting transfer from surfaces (Transfer and Food studies). The Test House 
study investigated the fate and transport of chlorpyrifos following a crack and crevice 
application and provided valuable information on spatial and temporal variability of 
surface concentrations in the absence of human activity. 


6 


During these studies, the following types of measurements were collected (not all types of 
samples were collected in all studies): 

• Air (indoor and outdoor) 

• Soil 

• House dust - Floors (carpet and hard surface) 

• Surface wipes (including eating and food preparation surfaces) 

• Transferable residues ( e.g ., polyurethane foam roller, Cl8 press) 

• Hand wipes 

• Dermal surrogates (cotton garment and socks) 

• Duplicate diet (solid food, beverages) 

• Handled food 

• Urine 

Information was also typically collected by questionnaire on: 

• Housing characteristics 

• Participant characteristics 

• Children’s activities (timelines and logs) 

• Recent pesticide use 

The types of media sampled and questionnaires administered in each study are listed in Table 
1.1. Other than the pesticide inventory and use questionnaires, questionnaire data are not the 
focus of this document. 

1.6 Pesticides of Interest to this Report 

The studies presented here were performed when a number of organophosphate and pyrethroid 
pesticides were in use; thus numerous pesticides from various chemical classes (including 
insecticides and herbicides) were measured. All measured insecticides (and insecticides 
synergists) are listed in Table 1.2, although not all of the studies collected data for all of the 
insecticides listed. To reduce complexity, this report focuses on the most commonly detected 
organophosphate and pyrethroid insecticides: 

• Chlorpyrifos 

• Diazinon 

• Permethrin 

• Cyfluthrin 


7 



Table 1.1 Available media, participant characteristics, and activities by study. 



NHEXAS-AZ 

MNCPES 

CTEPP 

ccc 

JAX SCREENING 

JAX AGGREGATE 

CHAMACOS 

CPPAES 

TESTHOUSE 

PET 

DIYC 

DAYCARE 

Air - Indoor 



S 



✓ 

V 



S 



Air - Outdoor 

V 

✓ 

V 



V 

S 






House Dust 

S 


V 




V 






Surface Residue Wipes 

V 


S 

✓ 



V 



S 

V 


LWW Surface Sampler 













Transferable Residues 

V 


V 




S 



V 

V 


Hand Wipes 

V 

V 

S 





✓ 


S 

V 

V 

Cotton Garments/Socks 







V 



S 


V 

Soil 


S 

S 

V 



V 



S 



Duplicate Diet 

S 

S 

V 



V 





S 


Handled Foods 











V 


Urine 

S 

S 

/ 



V 


V 


S 

V 


Housing Characteristics 

V 

V 

V 

V 


V 

V 

V 

V 

S 

V 


Participant Characteristics 

V 

S 

V 

V 

✓ 

S 


V 


S 

V 

S 

Children’s Activities 

V 

V 

V 



V 


S 


S 

V 

V 

Recent Pesticide Use 


S 

V 

V 

V 

V 







Pesticide Inventory 


V 



V 

V 








Table 1.2 Pesticides and metabolites measured in the studies. 


Pyrethroid 

Organophosphorus 

Other 

Allethrin 

Acephate 

Ethyl parathion 

Fipronil 

Bifenthrin 

Azinphos-methyl 

Fonofos 

Piperonyl butoxide 

Cyfluthrin a 

Chlorpyrifos a 

Malathion 

TCPy 

Cyhalothrin 

Chlorpyrifos-oxon 

Malathion-oxon 

IMP ac 

Cypermethrin 

Demeton-S 

Methamidophos 

3-PBA ad 

Deltamethrin 

Diazinon a 

Methidathion 


Esfenvalerate 

Diazinon-oxon 

Methyl-parathion 


Permethrin a 

Dichlorvos 

Mevinphos 


Pyrethrins 

Dimethoate 

Naled 


Resmethrin 

Disulfoton 

Phosmet 


Sumithrin 

Ethion 



Tetramethrin 




Tralomethrin 





a Pesticides and metabolites of primary interest in this document 
b 3,5,6-Trichloro-2-pyridinol, a selective metabolite of chlorpyrifos 
c 2-Isopropyl-4-methyl-6-hydroxypyrimidine, a specific metabolite of diazinon 
d 3-phenoxybenzoic acid, a metabolite common to many pyrethroids 


8 




























































1.7 Summary Descriptions of the Studies 

Individual study details are listed in Appendix B. Journal articles presenting results of these 
studies are listed in the Bibliography. The studies are summarized below. 

The National Human Exposure Assessment Survey in Arizona (NHEXAS-AZ) was performed in 
collaboration with the University of Arizona, the Illinois Institute of Technology, and Battelle 
Memorial Institute. Probability-based samples were collected in each of Arizona’s 15 counties 
from December 1995 to March 1997. Although 176 households participated, this report only 
includes data from 21 households with children ages 6-12 as primary participants. Environ¬ 
mental samples included indoor and outdoor air (3-day integrated samples), personal air (1-day), 
vacuumed surface dust, and window sill wipes. Personal samples included 24-hour duplicate 
diet and hand wipes. Biological samples consisted of urine samples (first morning void). 
Baseline and follow-up questionnaires and time-activity diaries captured activity patterns. Two 
pesticides (and their metabolites) were of primary interest, namely chlorpyrifos (TCPy) and 
diazinon, and two pesticides (and their metabolites) were of secondary interest, namely 
malathion (MDA) and carbaryl (1-naphthol). 

The Minnesota Children’s Pesticide Exposure Study (MNCPES) was an observational measure¬ 
ment study performed in collaboration with Research Triangle Institute (RTI), the Environmental 
and Occupational Health Sciences Institute (EOHSI), the Minnesota Department of Health, and 
the University of Minnesota. A telephone survey and in-home interviews were used to collect 
data on pesticide storage and use patterns from 308 households in both urban centers (Minneap¬ 
olis/St. Paul) and rural counties (Goodhue and Rice) during the summer of 1997. Probability- 
based sampling weights were developed and intensive environmental and personal monitoring 
were performed for 102 children, ages 3-13. Households reporting more frequent pesticide use 
were oversampled. Environmental samples included personal, indoor, and outdoor air (6-day 
integrated), surface dust (wipe and press), surface soil, and tap water. Personal samples included 
solid food (4-day composite), beverages (4-day composite), hand rinse, and first morning void 
urine (days 3, 5, and 7). In addition to questionnaires and diaries, videotaping was performed in 
a subset of 20 homes. Four primary pesticides (and their metabolites), namely chlorpyrifos 
(TCPy), atrazine (atrazine mercapturate), malathion (malathion dicarboxylic acid), and diazinon, 
and 14 secondary pesticides were measured, along with 13 polycyclic aromatic hydrocarbons 
(PAHs). 

The Children’s Total Exposure to Persistent Pesticides and Other Persistent Organic Pollutants 
(CTEPP) Study (Morgan et al., 2004) was performed in collaboration with Battelle Memorial 
Institute as an observational study of preschool children’s exposure to contaminants in their 
everyday environments (i.e., homes and daycare centers). Monitoring was performed from July 
2000 to March 2001 in North Carolina (spanning summer, fall, and winter) and from April 2001 
to November 2001 in Ohio (spanning spring, summer, and fall). The study population consisted 
of 257 children, ages 18 months to five years, and their primary adult caregivers (130 children, 
130 homes, and 13 daycare centers in North Carolina; 127 children, 127 homes, and 16 daycare 
centers in Ohio). Samples were collected over a 48-hr period at each home and daycare center, 
including indoor air, outdoor air, floor dust, soil, hand wipe, solid food, liquid food, and urine. 
Supplemental information included a recruitment survey, a house/building characteristics survey, 
pre- and post monitoring questionnaires, and activity and food diaries. In addition, 20% of the 


9 


OH participants were videotaped at home for about 2 hours. Additional samples (hard floor and 
food preparation surface wipes and transferable residues) were collected if the participant 
reported indoor or outdoor applications of pesticides within 7 days of the monitoring period. 

The First National Environmental Health Survey of Child Care Centers (CCC) was performed in 
collaboration with HUD (US Department of Housing and Urban Development) and CPSC (US 
Consumer Product Safety Commission). Samples were collected from August through October 
(summer and fall) 2001, at 168 randomly-selected child care centers nationwide. Many facilities 
reported recent pesticide application (either by professionals or by employees). Samples 
included soil, surface wipes, and transferable residues (Cl8 Press). A multi-residue chemical 
analysis method was used to measure a large suite of current-use pesticides. The study aimed to 
collect data on pesticide use practices and to characterize the distributions of pesticide 
concentrations in a nationally-representative sample of child care centers in the U.S. 

The study titled Biological and Environmental Monitoring for Organophosphate and Pyrethroid 
Pesticide Exposures in Children Living in Jacksonville, Florida (JAX) was performed in collab¬ 
oration with CDC (Centers for Disease Control and Prevention) and DCHD (Duval County 
Health Department) in Jacksonville (Duval County), Florida, from August through October 
(summer and fall) 2001. The CDC performed a biomonitoring study to measure metabolites of 
organophosphate and pyrethroid pesticides in a sample of 200 children who were 4-6 years of 
age. The DCHD conducted a home screening survey in a subset of 42 of the homes. The 
screening phase employed a pesticide screening inventory, surface wipes, and urine collection. 
The EPA conducted an observational study in a subset of nine of the homes to evaluate sampling 
and analysis methods and protocols for conducting aggregate exposure estimates for children. 
The aggregate exposure study included the pesticide screening inventory, surface wipes, indoor 
and outdoor air, cotton garment, duplicate diet, and transferable residue measurements, a time 
activity diary, and a urine sample. 

The Center for the Health Assessment of Mothers and Children of Salinas (CHAMACOS) 
Quantitative Exposure Assessment Study was a collaboration with the University of California at 
Berkeley. This observational study was performed in homes of agricultural workers living in 
Salinas, California. Twenty households with children ages 5 months to 3 years old (10 female 
and 10 male) were monitored during the period of June to October (summer and fall) 2002. 
Samples were collected over a 24-hour monitoring period and included indoor and outdoor air, 
house dust, transferable residues from floors (surface wipes and press samples), transferable 
residues from toys (surface wipes), urine, and cotton union suits and socks. A time/activity diary 
was also administered. The objective of the study was to evaluate sampling and analysis 
methods and study protocols that might be applied in larger studies such as the National 
Children’s Study. 

The Children’s Pesticide Post-Application Exposure Study (CPPAES) was a collaborative field 
study with EOHSI (Environmental and Occupational Health Sciences Institute) in urban New 
Jersey over a two-year period stretching from April 1999 to March 2001. Ten homes with 
children 2-5 years of age participated. Each of the homes had a professional “crack and 
crevice”-type application of a chlorpyrifos-based formulation at the time of the study, but only 
trace amounts of chlorpyrifos were applied in three of the homes. The monitoring period 
typically lasted for two weeks with pre- and multiple post-application samples. Sampling was 


10 


comprehensive with indoor air, deposition coupons, surface samples (LWW, Lioy-Weisel- 
Wainman sampler), toys, hand wipes, urine, air exchange rate, and time activity diary data 
collected throughout the study, and additional samples consisting of surface wipes, dermal 
wipes, cotton garments, and videotaped activities collected on the second day of the study. 

A field laboratory study titled the Distribution of Chlorpyrifos Following a Crack and Crevice 
Type Application in the US EPA Indoor Air Quality Research Test House (Test House) was 
performed in collaboration with the National Risk Management Research Laboratory (NRMRL). 
The Test House is an unoccupied three-bedroom house in Cary, NC. The study investigated the 
translocation of chlorpyrifos and the spatial and temporal variability of chlorpyrifos levels in air 
and on surfaces following a professional “crack and crevice”-type application onto the floor and 
cabinetry of a kitchen. Samples included air, polyurethane foam (PUF) roller, carpet sections, 

Cl8 surface press, and surface wipes from multiple rooms. Samples were collected pre¬ 
application and on days 1, 3, 7, 14 and 21 post-application. 

The Pilot Study Examining Translocation Pathways Following a Granular Application of 
Diazinon to Residential Lawns (PET) was performed during spring 2001 in six residential homes 
within a 50-mile radius of Durham, NC. Measurements were performed at homes where a 
homeowner applied a turf application of a granular formulation of diazinon. Sampling included 
indoor air (multiple rooms), PUF roller (outdoor and indoor), soil, doormat, high-volume small 
surface sampler (HVS3), dermal surrogate (cotton gloves), urine (adult and child), dog fur 
clippings, dog paw wipes, dog blood, and videotaping (15-min). Samples were collected pre¬ 
application and 1,2,4 and 8 days post-application. A feasibility study was also performed in a 
single home. The study focused on pesticide translocation and exposure pathways. 

The Dietary Intake of Young Children (DIYC) study was a small observational field study in 
collaboration with RTI. It included three homes where diazinon had been applied (two homes 
with commercial crack and crevice applications and one home with non-professional application) 
and took place between November 1999 and January 2000 (fall and winter). Collected samples 
included indoor air, outdoor air, surface wipes, hand wipes, surface press, food press, food 
samples, PUF roller, entry wipe, and urine. A primary goal of the study was to evaluate the 
potential for exposure to pesticides due to food preparation and handling in the home. 

The Feasibility of the Macroactivity Approach to Assess Dermal Exposure (Daycare) study was 
another collaboration with RTI (Cohen Hubal et al ., 2006). In this field study, nine daycare 
centers were identified that reported routine pesticide applications as part of the center’s pest 
control program. In each daycare, screening sampling was conducted to evaluate the distribution 
of transferable pesticide residues on floor surfaces in the area where children spent the most 
time. One daycare was selected for more intensive monitoring during the summer of 2001, 
following a series of regularly scheduled (monthly) applications. Surface sampling and 
videotaping of activities were conducted simultaneously with dermal surrogate (cotton garment) 
sampling to calculate dermal transfer coefficients. 

The Characterizing Pesticide Residue Transfer Efficiencies (Transfer) studies evaluated 
parameters that are believed to affect residue transfer from surface-to-skin, skin-to-object, skin- 
to-mouth, and object-to-mouth. The collaboration with Battelle was a series of controlled 
laboratory studies using fluorescent tracers as surrogates for pesticide residues. The protocol 


11 


involved applying fluorescent tracers to surfaces of interest as a residue at levels typical of 
residential pesticide applications, and then conducting controlled transfer experiments varying 
six parameters in a systematic fashion. Repetitive contacts with contaminated surfaces were 
used to measure the following transfers: hand to clean surface, hand to washing solution, and 
hand to mouth. In the mouthing trials, mouthing was simulated using saliva-moistened PUF 
material to measure mass of tracer transferred. Laboratory evaluations were performed to relate 
transfer of tracer to transfer of pesticides (Ivancic et al., 2004; Cohen Hubal et al ., 2005). 

The Food Transfer Studies were controlled laboratory experiments investigating pesticide 
transfer from household surfaces to foods and evaluating factors that have been identified as 
important, including surface type, duration of contact, surface loading, and contact pressure 
(applied force). Organophosphate, pyrethroid, and pyrazole insecticides were applied onto 
various household surfaces using a customized spray chamber. Pesticide transfer efficiencies 
were measured for three different foods, with standardized surface contact areas. Amounts of 
pesticide residue transferred to foods were compared to the amounts removed using surface 
wipes. Transfer efficiency (TE) was defined as the amount of pesticide recovered from the food 
item divided by the pesticide concentration or loading level. 

1.8 Exposure and Dose Models 

It is neither within the scope nor the intention of this report to provide a detailed discussion of 
the exposure and dose models that have been developed using these data or applied to these data. 
However, since human exposure research progresses through an iterative series of models and 
measurements, it is often necessary to refer to these models. Models are constructed using 
current knowledge and are subsequently used to identify areas of greatest uncertainty. Modeled 
results are used to direct the focus of the measurement studies to address those identified 
uncertainties. As newly collected data yields new knowledge, models are refined and the entire 
process repeats. At each iteration, real-world data replace default assumptions to produce more 
accurate assessments of exposure and risk. Throughout this document models are mentioned. 
“Algorithms” are the set of deterministic mathematical expressions developed in the Draft 
Protocol for Measuring Children’s Non-Occupational Exposure to Pesticides by all Relevant 
Pathways (Berry et al. , 2001) to assess exposure by each route as a function of concentration and 
various exposure factors. The Stochastic Human Exposure and Dose Simulation (SHEDS) 
model (Zartarian et al. , 2000) is a physically-based, probabilistic model that predicts multimedia/ 
multipathway exposures and doses incurred eating contaminated foods, inhaling contaminated 
air, touching contaminated surfaces, and ingesting residues from hand- or object-to-mouth 
activities. It combines information on pesticide usage, human activities, environmental concen¬ 
trations, and exposure and dose factors using Monte Carlo methods. The Exposure Related Dose 
Estimating Model (ERDEM) (Blancato et al ., 2004) is a physiologically-based pharmacokinetic 
(PBPK) model used to make reliable estimates of the chemical dose to organs of animals or 
humans. It solves a system of differential equations that describes the organ system, directly 
addressing the uncertainties of making route-to-route, low-to-high exposure, and species-to- 
species extrapolations when there are exposures to one or to multiple chemicals. The Children’s 
Dietary Intake Model (CDIM) (Hu et al., 2004) estimates total dietary exposure of children to 
chemical contaminants by accounting for excess dietary exposures caused by chemical 
contaminant transfer from surfaces and/or hands to foods prior to consumption. 


12 


2.0 PESTICIDE USE PATTERNS 


Very limited data are available to EPA researchers on what pesticides are currently being used in 
non-occupational environments, where they are being used, and the frequency of use. The EPA 
has not conducted a large scale survey to collect data on pesticide use patterns in the U.S. since 
1990, but use patterns are believed to have substantially changed since that time. The children’s 
observational studies described in this report collected information on household pesticide use as 
ancillary information that could be used to address this serious data gap. Despite the limited 
coverage of geographic regions, a relatively small number of study participants, and the general 
lack of knowledge about the active ingredients in brand name products on the part of consumers, 
valuable information was obtained. The NERL studies described in this section covered a period 
from 1997 to 2001. The indoor residential use of chlorpyrifos was cancelled while data 
collection was still ongoing in several studies (JAX, CCC, and CTEPP). 

The pesticides available to consumers or professionals for use in residential settings have 
changed over time. By the late 1980s the use of most organochlorine pesticides ( e.g ., DDT, 
chlordane, dieldrin, and heptachlor) was severely restricted in the U.S. The organophosphate 
(OP) insecticides (e.g., malathion, chlorpyrifos, and diazinon), appealing for their high insect 
toxicity, low costs, and low likelihood of pest resistance, quickly filled the void and became the 
pesticides of choice for both consumers and professional pest control operators (Karalliedde et 
al., 2001). The popularity of pyrethroid insecticides increased throughout the 1990s because of 
the following favorable properties: higher insecticidal toxicity, lower mammalian toxicity, and 
more rapid environmental degradation (Baker et al., 2004). Passage of the Food Quality 
Protection Act of 1996 led the EPA to consider aggregate childhood pesticide exposure. The 
OPs were the first class of pesticides whose tolerances were reassessed, leading to withdrawal of 
the registrations for indoor applications of chlorpyrifos and diazinon in 2001 and 2002, 
respectively, because of concern regarding the risk to children. Consequently, pyrethroids have 
become the leading residential insecticides. While household use of diazinon and chlorpyrifos is 
now restricted, these and other OPs are still widely used in agriculture, and some structural uses 
for chlorpyrifos, including the treatment of house foundations, are still approved. 

2.1 Sources of Information 

Important sources of information on pesticide use patterns in non-occupational environments 
include Market Estimates from EPA’s Office of Pesticide Programs (US EPA, 2004), national 
pesticide usage surveys, the Residential Exposure Joint Venture (REJV), the National Health and 
Nutrition Examination Survey (NHANES), and published scientific literature. 

The Office of Pesticide Programs uses proprietary data sources in producing “Market Estimates” 
of pesticide sales and use in various market sectors. According to their estimates, the annual 
amount of insecticide active ingredients used in the home and garden sector declined from 24 
million pounds in 1982, to less than 13 million pounds in 1988. Although the figure rose to 17 
million pounds between 1998 and 2001, it still represents a significant decline from the early 
1980s. In contrast, the amount of herbicides applied steadily increased over the same period, 
nearly doubling from 37 million pounds in 1982 to 71 million pounds in 2001 (US EPA, 2004) 


13 


as lawn coverage increased. In 2001, insecticides comprised nearly 60% and herbicides nearly 
30% of the home and garden sector expenditures (US EPA, 2004). 

The REJV is a program administered by eight pesticide registrants and is designed to provide 
home pesticide usage information critical for risk assessments on individual active ingredients as 
well as aggregate and cumulative risk assessments. Pesticide use by over 100,000 households in 
nine regions of the U.S. is recorded, with a year-long monthly diary of all residential pesticide 
applications in more than 4000 households. EPA expects to use the results of this 
comprehensive pesticide use survey to refine or replace many of its residential exposure default 
assumptions. Access to REJV results is restricted as confidential business information, thus only 
very limited data are publicly available. 

Results from two other national surveys are available: the National Household Pesticide Usage 
Study (US EPA, 1980; Savage et al ., 1981) and the National Home and Garden Pesticide Use 
Survey (US EPA 1992). The National Household Pesticide Usage Study (1976-1977) found that 
91% of the more than 8200 households surveyed reported using pesticides in their home, garden, 
or yard. According to the slightly more recent National Home and Garden Pesticide Use Survey 
(1990), 75% of American households reported using insecticides. These surveys, it should be 
noted, are old and the results are not considered relevant to current pesticide use patterns. 

NHANES is an ongoing assessment of the exposure of the U.S. population to environmental 
chemicals. Beginning with the 1999-2000 cycle, the interview included, at the request of EPA, 
questions on pesticide applications performed in the past month. According to the most recent 
survey (2001-2002), 18% of households used insecticides inside the home within the past month, 
nearly 40% of which were professional treatments. Of households with private yards, 20% 
reported pesticide applications in the yard during the month, roughly 36% of which were 
professional treatments. NHANES does not report results by region or by season. 

Studies in the open literature can also help to identify pesticide use patterns. Davis et al. (1992), 
Bass et al. (2001), Curwin et al. (2002), Freeman et al. (2004), and Carlton et al. (2004) address 
pesticide use patterns in various geographic locations within the U.S., including Missouri, 
Arizona, Iowa, Texas, and New York. 

A study conducted in Missouri from June 1989 to March 1990 using telephone interviews (Davis 
et al., 1992) examined pesticide use in the home, garden, and yard. Nearly all 238 families 
(98%) used pesticides at least one time per year, and two-thirds used pesticides more than five 
times per year. Pesticides were most commonly used inside the home (80%), followed by in the 
yard (57%). Flea collars were the most popular pest control product (50%). Diazinon and 
carbaryl were identified as the two most commonly used active ingredients at that time. 

The community-based survey conducted by Bass et al (2001) in Douglas, Arizona in 1999 
identified pesticides used in the home, use and storage locations, and disposal methods. All 
(100%) of the 107 randomly chosen study participants reported using pesticides in the six 
months prior to the survey, although only 75% reported pest problems. Over 30% used a 
professional exterminator. A total of 148 pesticide products, representing more than 50 unique 
active ingredients, were catalogued (1.4 products per home). The synergist piperonyl butoxide 


14 


(34%) was most common, followed by pyrethrins (24%), permethrin (18%), allethrin (17%), 
diazinon (16%), and boric acid (13%). The majority of the pesticides were stored inside the 
house (70%), typically in the kitchen (45%). 

Curwin et al. (2002) investigated the differences in pesticide use for 25 farm homes and 25 non¬ 
farm homes in Iowa. The target pesticides included atrazine, metolachlor, acetochlor, alachlor, 
2,4-D, glyphosate, and chlorpyrifos. Among the non-farm households, 84% used pesticides in 
their homes or on their lawns or gardens. Only 17% of reported residential pesticide use was by 
commercial application. 

Freeman et al. (2004) examined pesticide use patterns during the summer 2000 and winter 2000- 
2001 seasons among families with very young children in a Texas border community. Pesticide 
use inside the home showed seasonal variation (82% of homes treated in summer versus 63% in 
winter). The primary room treated was the kitchen, and the primary structures treated were the 
floors, lower walls, and dish cupboards. The pesticides used were typically pyrethroid 
formulations. For nearly all of the pesticides analyzed, no differences were found in pesticide 
levels in house dust based on family reports of pesticide use in the home or yard. 

Carlton et al. (2004) surveyed stores in New York City, NY in mid-2003 to determine whether 
the phase-out of chlorpyrifos and diazinon had been effective and what alternative pesticides 
were available. The authors found the phase-out to be more effective for chlorpyrifos than for 
diazinon. The summer after chlorpyrifos sales were to have ended, chlorpyrifos-containing 
products were found in only 4% of stores that sold pesticides; however, after diazinon sales were 
to have ended, 18% of stores surveyed, including 80% of supermarkets, still stocked diazinon- 
containing products. Lower toxicity pesticides, including gels, bait stations, and boric acid, were 
available in only 69% of the stores and were typically more expensive. 

The children’s exposure research program collected pesticide use information from homes and 
daycare centers in the MNCPES, JAX, CTEPP, CCC, and Daycare studies. Information on 
collection methods is available in Table 2.1. In the context of this report, pesticide use patterns 
include application frequency, locations, types, methods and active ingredients, as well as 
pesticides identified in inventories and detected in screenings. The following are highlights of 
the data collected on pesticide use patterns in these studies. A thorough discussion of MNCPES 
storage and use patterns is found in Adgate et al. (2000). 


15 


Table 2.1 Pesticides use information collection methods. 


Study 

Year 

Setting 

Inventory 

Questionnaire 

Screening 

Wipes 

MNCPES 

1997 

Residence 

Brand name, type, EPA 
registration number, use in 
past year. 

Baseline usage (past year) by 
participant recollection. Recent 
use (past week and during 
monitoring period). 

No 

CTEPP 

2000- 

2001 

Residence and 
Daycare 

Center 

None 

Baseline usage (ever) of 
insecticides, herbicides, 
fungicides, or shampoos. Recent 
use (past week) of any pesticide. 

No 

CCC 

2001 

Daycare 

Center 

None 

Usage frequency (categories) 
and locations for specific active 
ingredients. Questionnaire 
administered to Center Director 
or professional applicator. 

Yes 

JAX 

2001 

Residence 

Brand name, type, EPA 
registration number. 

Use in past 6 months, use 
frequency, use location, and 
targeted pest noted for each 
product. 

Usage frequency (categories), 
locations, application methods, 
and anticipated future use. 

Yes 

Daycare 

2000 

Daycare 

Center 

None 

Specific active ingredient 
verified by professional 
applicator. 

Yes 


16 














2.2 Application Frequency 

The frequency of pesticide application, typically over the past month or year, is generally 
gathered through questionnaires. Although there is little supporting empirical evidence, it is 
believed that the frequency of application, along with the form and chemical properties of the 
pesticide, is an important determinant of indoor air and surface concentrations. It is assumed that 
residue levels within a residence will rise with increasing pesticide application frequency. 
Conversely, infrequent pesticide application is assumed to decrease the likelihood of measuring 
pesticide residues. Arguably, the more frequently pesticide applications occur, the more likely 
the occupant is to have contact with pesticide residue. 

• As presented in Table 2.2, about 20% of study participants in Jacksonville, FL (JAX) 
reported using pesticides in the past seven days (August to October 2001) compared to 
14% in CTEPP-NC (July 2000 to March 2001), 13% in CTEPP-OH (April to November 
2001), and only 10% in Minnesota (MNCPES) (May to August 1997). This provides 
some evidence of a pattern of higher application frequencies in warmer climates. The 
North Carolina study was the only one to include winter months; the percentage would 
likely be higher if winter months were excluded. 

• About the same proportion (unweighted) of participants that used pesticides in the past 
month (or planned to use them in the next month) in JAX (51%), used them in the past 
six months in MNCPES (52%). The percentage of JAX participants is substantially 
higher than 18-23% reporting insecticide use in the past month in NHANES (Table 2.2). 

• Differences according to geographical region become more evident in the CTEPP studies 
(Table 2.3) when focusing on insecticides and rodenticides, as 74% of the participants in 
warmer climate North Carolina reported using insecticides or rodenticides compared to 
only 51% in colder climate Ohio. 

• In Minnesota (MNCPES), 88% of the participants used pesticides in the past year, 
slightly more than the 84% reported by Curwin et al. (2002) in Iowa but less than the 
98% reported by Davis et al. (1992) in Missouri and the 100% reported by Bass et al. 
(2001) in Arizona. 

• In the CCC study, 74% of the facilities reported application of pesticides in the last year 
(63% reported interior and 42% reported exterior applications), and 7% were unsure if 
any application occurred. Up to 107 pesticide applications per year were reported. 

• About a third of the interior and a quarter of the exterior applications in the nationwide 
CCC study were performed on a monthly basis. In the Daycare study, monthly or more 
frequent pesticide applications were anecdotally found to be standard practice in the 
Raleigh-Durham area of North Carolina. 


17 




Table 2.2 Proportion (unweighted) of participants reporting pesticide use by study. NHANES 
participant responses are included for comparison. 


Study 

Use within the past 
seven days 

Use within the past 
one month 

Use within the past 
six months 

CTEPP-NC 

14% 

a 

— 

CTEPP-OH 

13% 

— 

— 

JAX 

20% 

51% 

— 

MNCPES 

10% b 

— 

52% 

NHANES 99-00 

— 

23% c 

— 

NHANES 01-02 

— 

18% c 

— 


a Information not available 
b Recruited households 
c Restricted to use inside of home 


Table 2.3 The proportion of CTEPP participants reporting use of four types of pesticides. 


Type of Pesticide 

North Carolina 

Ohio 

Herbicides 

38% 

50% 

Insecticides / Rodenticides 

74% 

51% 

Fungicides 

6% 

4% 

Shampoos / Lotions 

8% 

9% 


18 






















2.3 Application Locations 


Although applied pesticides are redistributed throughout a home following an application, a 
concentration gradient exists with higher concentrations in the application room and lower 
concentrations in more distant rooms (Stout and Mason, 2003). Since residential applications 
may be performed by someone other than the occupant (< e.g ., professional pest control service, 
gardener, lawn service, or property management), the occupant may not know which locations 
were treated. 


• In JAX, 58% reported treating all rooms in the home, and 15% reported treating just the 
kitchen. 

• The most commonly treated room in the CCC study was the kitchen (62%), followed by 
the bathroom (52%) (Figure 2.1). All rooms were treated in 23% of the centers. 

• Areas treated by professional crack and crevice applications in CPPAES represented 93% 
of the homes’ living areas. 





purpose room sampled 

room rooms 


Room 


Figure 2.1 Weighted percentage of child care centers reporting treatment of various rooms in the 
Child Care Centers (CCC) study. 


19 























2.4 Application Types and Methods 

The three common types of pesticide applications in the non-occupational environment are 
broadcast, total release aerosol, and crack-and-crevice. A broadcast application spreads 
insecticide onto broad surfaces, typically large sections of walls, floors, ceilings, or in and 
around trash containers (Rust et al ., 1995). Total release aerosols, also known as “foggers” or 
"bug bombs," contain propellants that release their contents at once to fumigate a large area. 
Alternatively, a crack-and-crevice application is the application of small amounts of insecticide 
into areas where pests typically harbor or enter a building. Cracks and crevices are commonly 
found between cabinets and walls, at expansion joints, and between equipment and floors (Rust 
et al ., 1995). Crack and crevice type applications, which usually produce lower airborne 
concentrations and surface loadings than broadcast or total release type applications, are favored 
by professional pest control services. 

Method of pesticide application (as differentiated from “type” of application) refers to the 
equipment or product form used, and may include aerosol sprayer, hand pump sprayer, hose end 
sprayer, spritz sprayer, hand trigger sprayer, liquid, fogger, gel, granules/dust/powder/pellets, 
lotion, shampoo, bait station/trap, candle/coil, fly strip, pet collar, and spot-on pet treatment. 

• Only very limited information on application type and method was collected in any of the 
field study questionnaires. 

• In CCC, 36% of the interior applications were reported by the center directors as crack 
and crevice, and only 2% were reported as broadcast. In the Daycare study, all observed 
pesticide applications were crack and crevice. 

• The most common application methods reported in JAX were as follows: 37% hand 
pump sprayer, 24% aerosol can, 3% fogger, and 3% bait. 

• Applications in JAX were more likely to be performed by the respondent or respondent’s 
family member (41%) than by a professional service (35%). These results are similar to 
NHANES 01-02, where 66% of the survey respondents reported non-professional 
treatments compared to professional treatments that were reported by 40% of the 
respondents. These results are also similar to the survey by Bass et al (2001) in Douglas, 
Arizona, where 30% used professional services. 

2.5 Pesticides Identified in Inventories, Records and Wipe Samples 

• Pesticide products were found in 86% of the 36 homes inventoried in the JAX study 
(Table 2.4), with up to three products per household. Pyrethroids were the most common 
active ingredient (67% of homes), primarily cypermethrin (25%) and allethrin (12%), 
followed by imiprothrin, pyrethrins, and tralomethrin (all 14%). Only one 
organophosphate insecticide (diazinon) and one insect repellent (DEET) were found. 

• The most commonly inventoried pyrethroids in JAX (Table 2.4) corresponded well with 
commonly reported pyrethroids in the Residential Exposure Joint Venture (Table 2.5). 

• Cataloguing of pesticides in the CCC study (Table 2.6) gave results similar to JAX, with 
pyrethroid products most commonly identified (second only to products with unknown 


20 


active ingredients). 

• The finding of 145 application events (Table 2.6) with unidentified active ingredients in 
the CCC study suggests that tracking of pesticide use in and around daycare facilities 
may require improved recordkeeping. 

• As reported in Adgate et al. (2000), pesticide products were found in 97% (weighted) of 
the MNCPES households. The weighted mean number of pesticide products used per 
household was 3.1. Participants reported that fewer than 25% of the pesticides 
inventoried in their homes were used during the past year. 

• In MNCPES, DEET-containing products were used in 47% of the homes during the last 
year (Table 2.7). 

• Repellents, pyrethrins and pyrethroids, organophosphates, chlorophenoxy herbicides, and 
carbamates were present in more than 20% of the MNCPES households (Table 2.7). 

• In the Daycare study, professional pest control services applied pyrethroid or pyrethrin 
pesticides in six of the eight facilities (data not presented). Esfenvalerate was applied in 
two facilities while cyhalothrin, pyrethrins, cypermethrin, and tralomethrins were each 
used in one. 

• Cypermethrin, c/s-permethrin, and /ra/zs-permethrin were detected in over 80% of the 
surface wipe samples collected in 46 homes in JAX (Table 2.8), consistent with the 
pesticide inventories. Chlorpyrifos and diazinon, although not identified in the 
inventories, were present in 89% and 91%, respectively, of the surface wipe samples. 

• Permethrin and cypermethrin were the most frequently detected pyrethroid pesticides in 
both JAX (homes) and CCC (childcare centers) (Table 2.8). Chlorpyrifos and diazinon 
were the most frequently detected OPs, at frequencies comparable to permethrin. 

• As of 2001, the synthetic pyrethroids appeared to be the most frequently used insecticides 
for indoor applications in homes and child care centers. It is anticipated that their use has 
become even more common since the cancellation of indoor use registrations of 
chlorpyrifos (2001) and diazinon (2002). 

2.6 Demographic Factors Influencing Applications 

• As reported by Adgate et al., (2000), there were no statistically significant differences in 
the weighted total number of products found or reportedly used in MNCPES based on 
either population density (urban versus non-urban households) or other socio¬ 
demographic factors including race, ethnicity, home type, income, and level of education. 

• Chi square analysis of CTEPP data (not presented) found no association between having 
applied pesticides within the past week and either income class or urban/rural status. 


21 



Table 2.4 Pesticides inventoried in 36 households in Jacksonville, FL (JAX) in fall 2001. 


Active Ingredient 

Pesticide Class 

Number of Homes Where 
Found (% of Homes) 

Cypermethrin 

Pyrethrins/Pyrethroids 

9 (25%) 

Allethrin 

Pyrethrins/Pyrethroids 

8 (22%) 

Pyrethrins 

Pyrethrins/Pyrethroids 

5 (14%) 

Imiprothrin 

Pyrethrins/Pyrethroids 

5 (14%) 

Tralomethrin 

Pyrethrins/Pyrethroids 

5 (14%) 

MGK 264 a 

Synergist 

4(11%) 

Permethrin 

Pyrethrins/Pyrethroids 

4(11%) 

Fipronil 

Phenylpyrazole 

4(11%) 

Piperonyl butoxide 

Synergist 

4(11%) 

Hydramethylnon 

Aminohydrazone 

3 (8%) 

Tetramethrin 

Pyrethrins/Pyrethroids 

3 (8%) 

Cyfluthrin 

Pyrethrins/Pyrethroids 

2 (6%) 

Esfenvalerate 

Pyrethrins/Pyrethroids 

2 (6%) 

Prallethrin 

Pyrethrins/P yrethro ids 

2 (6%) 

Bifenthrin 

Pyrethrins/Pyrethroids 

1 (6%) 

DEET 

Repellent 

1 (6%) 

Diazinon 

Organophosphate 

1 (6%) 


a N-octyl bicycloheptene dicarboximide 


Table 2.5 Most commonly applied pyrethroids in 1217 households with complete 12 month 
REJV survey data, as reported by Ozkaynak (2005). 


Pyrethroid Pesticide 

Number of Homes Where 
Applied (% of Homes) 

Permethrin 

518(43%) 

Pyrethrins 

472 (39%) 

Piperonyl Butoxide 

461 (38%) 

Allethrin 

437 (36%) 

Tetramethrin 

342 (28%) 

Phenothrin 

293 (24%) 

Tralomethrin 

279 (23%) 

Cypermethrin 

163 (13%) 

Resmethrin 

106 (9%) 

Bifenthrin 

99 (8%) 

Cyfluthrin 

46 (4%) 

Fenvalerate 

37 (3%) 

Esfenvalerate 

25 (2%) 

Deltamethrin 

22 (2%) 

Prallethrin 

13 (1%) 

Cyhalothrin 

4 (<1%) 


22 









































Table 2.6 Number of pesticide products applied during one year (2001) in 168 child care centers 
(CCC), as reported by the center directors and/or professional applicators. 


Pesticide Class or Type 

Number of Products Applied in Past Year 
(Unweighted % of All Products) 

Unknown 

• 145 (39%) 

Pyrethroids 

93 (25%) 

Phenyl pyrazole or unclassified insecticide 

44 (12%) 

Pesticide mix 

22 (6%) 

Fungicide/insecticide 

20 (5%) 

Organophosphate 

10 (3%) 

Glueboard/Mouse traps 

7 (2%) 

Carbamates 

6 (2%) 

Juvenile hormone mimic insecticide 

6 (2%) 

Coumarin rodenticides 

5 (1%) 

Herbicides 

3 (1%) 

Insecticides 

3 (1%) 

Unclassified acaricide 

3 (1%) 

Unclassified insecticide 

3 (1%) 

Biopesticides 

2 (1%) 

Pheromone 

1 (<1%) 

Phosphoramidothioate acaricide 

1 (<1%) 

Rodenticides 

1 (<1%) 


Table 2.7 Pesticides inventoried and used in 308 households in Minnesota (MNCPES) in 
summer 1997 (adapted from Adgate et al., 2000). 


Active Ingredient 

Pesticide Class 

Homes Where Found 
(Weighted Percent) 

Homes Where Used 
in the Past Year 
(Weighted Percent) 

DEET 

Repellent 

196 (58%) 

162 (47%) 

Piperonyl butoxide 

Synergist 

152 (45%) 

91 (25%) 

Pyrethrins 

Pyrethrins/Pyrethroids 

147 (43%) 

88 (25%) 

MCPA 

Chlorphenoxy herbicide 

107 (35%) 

55 (17%) 

Permethrin 

Pyrethrins/Pyrethroids 

93 (35%) 

65 (15%) 

Chlorpyrifos 

Organophosphate 

89 (29%) 

55 (17%) 

Propoxur 

Carbamate 

84 (25%) 

53 (17%) 

MGK 264 a 

Synergist 

83 (25%) 

43 (12%) 

Allethrin 

Pyrethrins/Pyrethroids 

81 (24%) 

49 (13%) 

2,4-D 

Chlorphenoxy herbicide 

74 (23%) 

37(11%) 

Diazinon 

Organophosphate 

65 (18%) 

37(11%) 

Glyphosoate 

Aminophosphate 

62 (18%) 

37 (12%) 

Tetramethrin 

Pyrethrins/Pyrethroids 

62 (18%) 

32 (8.5%) 

Resmethrin 

Pyrethrins/Pyrethroids 

60 (20%) 

24 (8.1%) 

Carbaryl 

Carbamate 

50 (14%) 

24 (5.4%) 


a N-octyl bicycloheptene dicarboximide 


23 















































Table 2.8 Detection frequencies of target analytes in soil and wipe samples in the CCC study 
(weighted) and in screening wipe samples collected in JAX (unweighted). 



CCC 

JAX 

Compound 

% Detect in 

Soil Samples 

% Detect in Floor 
Wipes 

% Detect in 
Surface Wipes 

% Detect in 
Surface Wipes 

PYRETHROIDS 

c/s-Allethrin 

5 

2 

0 

22 

/ra«.s-Allethrin 

5 

2 

0 

22 

Bifenthrin 

14 

5 

4 

20 

Cyfluthrin 

7 

7 

1 

20 

/am6</a-Cyhalothrin 

6 

7 

5 

9 

Cypermethrin 

8 

23 

9 

80 

Delta/T ralomethrin 

5 

2 

0 

15 

Esfenvalerate 

9 

6 

0 

30 

c/s-Permethrin 

12 

63 

48 

89 

/rans-Permethrin 

15 

64 

64 

87 

Resmethrin 

5 

3 

6 

0 

Sumithrin 

5 

2 

1 

4 

Tetramethrin 

5 

2 

0 

13 

ORGANOPHOSPHATES 

Acephate 

50 

3 

0 

7 

Azinphos methyl 

15 

1 

0 

2 

Chlorpyrifos 

21 

67 

76 

89 

Chlorpyrifos oxon 

11 

1 

1 

0 

Demeton S 

11 

0 

0 

0 

Diazinon 

19 

53 

43 

91 

Diazinon oxon 

13 

17 

8 

17 

Dichlorvos 

11 

0 

0 

2 

Dimethoate 

11 

1 

0 

0 

Disulfoton 

11 

0 

0 

0 

Ethion 

11 

1 

0 

2 

Ethyl parathion 

11 

1 

0 

0 

Fonofos 

12 

0 

0 

0 

Malathion 

12 

18 

5 

20 

Malathion oxon 

11 

0 

0 

0 

Methamidophos 

11 

2 

1 

0 

Methidathion 

11 

1 

1 

0 

Methyl parathion 

11 

0 

0 

0 

m-Mevinphos 

11 

21 

7 

7 

/rans-Mevinphos 

11 

5 

0 

4 

Naled 

11 

0 

0 

0 

Phosmet 

11 

2 

0 

4 

OTHER PRODUCTS 


Fipronil 

11 

8 

10 

7 

Piperonyl butoxide 

12 

23 

11 

50 


24 

















































































3.0 AIR CONCENTRATION MEASUREMENTS 


3.1 Introduction and Data Availability 

Children are exposed to residential pesticides via the ingestion, dermal, and inhalation routes. Of 
these routes, inhalation is the best characterized and requires measurements that are simple to 
collect in field studies. Estimating absorption via inhalation relies on measured airborne 
chemical concentrations and on relatively few default exposure factor assumptions, such as the 
inhalation rate and time spent in specific locations. Since indoor pesticide concentrations are 
typically higher than outdoor concentrations, and since young children spend the majority of 
their time indoors, indoor concentrations account for the bulk of their inhalation exposure. 

Absorption via the inhalation pathway involves the uptake of vapors and particle-bound residues 
present in the air. It is generally assumed that inhaled vapors will be readily absorbed across the 
alveolar membrane into the bloodstream (at least for soluble compounds). Particle-bound 
residue may vary in size and composition, both of which may influence thoracic penetration and 
affect absorption. Inhaled particle-bound contaminants trapped in upper airway (nasal and upper 
lung) mucosa may also be subsequently ingested. 

The methods for measuring of airborne pesticide concentrations are well-developed and easily 
implemented indoors and outdoors using stationary or personal samplers. The methods involve 
collecting gases and/or particle-bound residues onto filters and sorbent media (the two are 
combined so that no distinction is made between gases and particle-bound residues). Stationary 
samplers are typically placed adjacent to treated areas and/or in the location where the participant 
spends the most time. Samplers may be placed at several locations throughout the home to 
investigate the spatial distribution of pesticides. Stationary samplers are located at specified 
heights above the floor to represent the assumed breathing area of the study participants. 

Personal samplers are worn by the study participants near the breathing zone. Either type of 
sampler may be modified with a size selective inlet to exclude specific particle size fractions. 
Sampling media vary but often consist of a pre-filter in tandem with a sorbent composed of 
polyurethane foam (PUF) or polymeric resin beads ( e.g ., XAD). 

The sampling approaches and methods for each study are described in Table 3.1. Since air 
sampling techniques are fairly standardized, the methods are consistent across studies. In the 
large observational field studies, air samples were collected over multiple days for reasons that 
included reducing measurement error due to day-to-day variability, improving detection limits, 
and reducing costs associated with changing and analyzing filters. The smaller, focused studies 
typically employed multiple, consecutive 24-hour sampling periods to capture temporal 
variability. Personal sampling was attempted in only one study, MNCPES, but compliance 
issues were noted. 

3.2 Pesticide Presence 

All pesticides included in this report have been used in residential settings. Because of the 
potentially long persistence of some pesticides in the indoor environment (Gurunathan et al., 
1998), they may be detected even in the absence of a recent application. Detection frequencies 
for indoor and outdoor samples are presented graphically in Figure 3.1. While detection 


25 


frequency corresponds inversely to the limit of detection (LOD), the LOD for each compound is 
relatively consistent across the large observational field studies. The exception to this is the 
NHEXAS-Arizona study, which employed a collection method with a relatively small sample 
volume, resulting in a higher LOD. The LODs for each pesticide by study are presented in Table 
3.2. 

• Detection limits (Table 3.2) varied by as much as an order of magnitude across studies. 
Within studies, detection limits were similar for organophosphate and pyrethroid 
insecticides. Detection limits are influenced by sample volume (Table 3.1). For 
example, the much lower detection limits for chlorpyrifos and diazinon in MNCPES 
compared to NHEXAS-AZ reflects the much larger volume sampled in MNCPES. 

• The compounds most frequently detected in indoor air (Figure 3.1) were the 
organophosphate (OP) insecticides chlorpyrifos, (typically > 90%) and diazinon 
(typically > 75%), followed by the pyrethroid insecticide permethrin (typically > 50%). 

• The insecticides most frequently detected in outdoor air (Figure 3.1) were also 
chlorpyrifos and diazinon, but the detection frequencies were lower and more variable 
across studies. 

• Chlorpyrifos was detected at a high frequency (Figure 3.1) even in those studies 
conducted after its indoor residential use was restricted (JAX and CHAMACOS). 

• The pesticide degradation products of chlorpyrifos and diazinon, TCPy and IMP, 
respectively, were frequently detected in air samples collected in CTEPP (Figure 3.1); 
none of the other studies included these as target analytes. 


26 


Table 3.1 Summary of air sample collection methods. 


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27 























Table 3.2 Limits of detection (ng/m 3 ) for air samples by compound and study. 


Compound 

Chlorpyrifos 

Diazinon 

cis- 

Permethrin 

trans- 

Permethrin 

Cyfluthrin 

TCPy 

IMP 

NHEXAS-AZ 

3.2 

2.1 

a 

— 

— 

— 

— 

MNCPES 

0.10 

0.10 

0.09 

0.09 

— 

— 

— 

CTEPP NC 

0.09 

0.09 

0.09 

0.09 

0.87 

0.09 

0.09 

CTEPP OH 

0.09 

0.09 

0.39 

0.33 

0.87 

0.09 

0.09 

JAX 

1.0 

0.4 

1.0 

1.0 

1.2 

— 

— 

CHAMACOS 

0.3 

0.3 

0.6 

0.6 

7.0 

-- 

— 

CPPAES 

2.0 

— 


— 

— 

— 

— 

DIYC 

— 

1.2 

— 

— 

— 

— 

— 

PET 

— 

1.0 

— 

— 

— 

— 

— 


a Blank cells (--) indicate that the pesticide or metabolite was not measured in the study. 


28 



















Detection Frequency in Indoor Air 



o 

a> 

•«-> 

o> 

a 



Chlorpyrifos TCPY Diazinon IMP 



I 

c-Perm t-Perm 


Cyfluthrin 


^^NHEXAS-AZ ^CTMNCPES 
^^JAX SmCPPAES 


CTEPP-NC C=CTEPP-OH ^^CHAMACOS 

EZZZ2 Test House ESS PET IZZ2DIYC 


Detection Frequency in Outdoor Air 


100- 

90- 

80- 

£ 70- 

>> 

o 

S 60. 

3 

cr 

® 50- 

LJL 

J 40 ' 

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© 

o 30- 

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10 - 


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IMP 


t- 


c-Perm t*Perm Cyfluthrin 


^^NHEXAS-AZ BCTMNCPES 


ICTEPP-NC 


ICTEPP-OH E2ZZ3CHAMACOS ^SJAX 


Figure 3.1 Frequency of detection of pesticides measured in indoor and outdoor air in selected 
studies. 


29 































































































3.3 Comparisons of Air Concentrations 

Previous studies have reported post-application concentrations of semi-volatile pesticides in air 
that may reach levels representing considerable exposure by the inhalation route (Byrne et al., 
1998; Fenske et al., 1990; Lewis et al., 2001). Low measurable airborne levels have also been 
reported even in the absence of a recent application event (Lewis et al., 1994; Whitmore et al., 
1994). Lognormal probability plots and box-and-whisker plots graphically depicting the 
(unweighted) measurements of compounds of interest in our studies are presented in Figures 3.2 
through 3.5. The median and 95 th percentile concentrations are presented in Table 3.3 (complete 
summary statistics are presented in Tables A.l through A.7 in Appendix A). 

• For pesticides measured in indoor and outdoor air, the observed concentrations typically 
approximate lognormal distributions, as demonstrated in the lognormal probability plots 
in Figures 3.2 and 3.3. 

• Despite differences in the lengths of the sample collection periods (1 to 7 days), the in¬ 
door chlorpyrifos concentrations observed across the large observational field studies are 
similar in their variability, as demonstrated by similar slopes in the probability plot 
(Figure 3.2). Similar variability over varying collection periods suggests that air 
concentrations are reasonably consistent from day-to-day in the absence of a recent 
application. 

• Comparison of air concentrations across studies in the box-and-whisker plots (Figure 3.4) 
finds that, as expected, pesticide concentrations in smaller studies, where measurements 
immediately followed an application, are much higher than in the larger observational 
field studies; for example, note the high indoor chlorpyrifos levels measured in CPPAES 
and the Test House. 

• Median concentrations are typically an order of magnitude higher indoors than outdoors 
(Table 3.3). Two notable exceptions are JAX and CHAMACOS. In the JAX samples, 
collected in a community with high year-round pesticide usage, outdoor diazinon and c/s¬ 
and fra/is-permethrin levels are nearly as high as indoor levels. In the CHAMACOS 
samples, collected in an agricultural community, median outdoor diazinon levels exceed 
indoor levels. 

• The low pesticide concentrations routinely measured outdoors (notwithstanding the 
exceptions noted above) together with the relatively short amount of time that young 
children typically spend outdoors suggest that inhalation of outdoor air is not an 
important contributor to their aggregate pesticide exposure. 

• The median indoor concentrations in the large observational field studies are higher for 
the organophosphates (OPs) than for the pyrethroids (Figure 3.4). Not only do OPs tend 
to have higher vapor pressure, but at the time these studies were conducted, OPs still 
dominated the marketplace. Detectable levels of chlorpyrifos and diazinon are likely to 
exist for some time after restriction of their indoor uses due continued use of existing 
home inventories and reemission from indoor surfaces serving as sinks (such as carpet). 


30 


• In indoor air measured in CTEPP (Figure 3.6), a relationship is evident between 
chlorpyrifos and its degradation product TCPy. The same is true for diazinon and its 
degradation product IMP. The nearly log-log relationship suggests a power relationship, 
and at the median level the degradate is present at about 25 to 30% of the concentration 
of its parent. Accordingly, the metabolites/degradates measured in urine may reflect 
exposure to both the parent pesticide and the degradate, not just to the parent compound 
as is often assumed. 

• Environmental concentrations of the degradation products were not measured in any of 
the small, pilot-scale studies, thus the degradate-to-parent ratio immediately following 
application is unknown. 


Table 3.3 Median and 95 th percentile air concentrations (ng/m 3 , unweighted) for frequently 
detected pesticides. 




Chlorpyrifos 

Diazinon 

m-Permethrin 

rrans-Permethrin 

Study 

Location 

P50 

P95 

P50 

P95 

P50 

P95 

P50 

P95 

NHEXAS-AZ 

Indoor 

3.37 

164.7 

5.59 

219.6 

a 

— 

— 

— 

Outdoor 

ND b 

ND 

ND 

ND 

— 

— 

— 

— 

MNCPES 

Personal 

1.52 

16.86 

0.28 

4.66 

0.20 

2.07 

<0.09 

1.72 

Indoor 

1.85 

30.25 

0.27 

8.59 

0.09 

1.26 

<0.09 

1.26 

Outdoor 

<0.10 

0.19 

<0.10 

0.22 

<0.09 

0.15 

<0.09 

0.48 

CTEPP-OH c 

Indoor 

1.75 

21.69 

0.97 

56.87 

0.28 

1.63 

0.23 

1.04 

Outdoor 

0.20 

1.13 

0.15 

1.49 

0.28 

0.95 

0.23 

0.66 

CTEPP-NC c 

Indoor 

6.07 

62.22 

2.03 

63.66 

0.41 

7.79 

0.27 

7.16 

Outdoor 

0.28 

3.99 

0.09 

0.98 

0.06 

0.47 

0.06 

0.30 

JAX 

Indoor 

20.37 

84.92 

4.64 

28.04 

0.71 

92.47 

3.06 

134.3 

Outdoor 

3.77 

6.62 

3.53 

6.76 

2.13 

2.29 

2.50 

10.24 

CHAMACOS 

Indoor 

1.90 

NA d 

1.80 

NA d 

0.50 

NA d 

<0.10 

NA d 

Outdoor 

0.90 

NA d 

2.80 

NA d 

0.10 

NA d 

<0.10 

NA d 

CPPAES e 

Indoor 

149.0 

815.6 

4.55 

23.88 

— 

— 

— 

— 

Test House e 

Indoor 

290.0 

1000 

— 

— 

~ 

— 

— 

— 

PET 

Indoor 

— 

— 

45.6 

562 

— 

— 

— 

— 

DIYC 

Indoor 

— 

— 

1800 

4900 

— 

— 

— 

— 


a Blank cells indicate the pesticide was not measured in the study 
b ND = not detected 

c CTEPP samples collected at both homes and daycares 
d NA = summary statistic not available at time the report was prepared 
e Day 1 measurements only, multiple rooms 


31 































CHLORPYRIFOS 
INDOOR AIR (ng/m3) 


CHLORPYRIFOS 
OUTDOOR AIR (ng/m3) 




+ + + NHEXAS—AZ 
* * * CTEPP-NC HOME 
o O O CTEPP-OH HOME 


XXX MNCPES 
□ □ □ CTEPP-NC DAYCARE 
AAA CTEPP-OH DAYCARE 


+ + + NHEXAS—AZ 
* * * CTEPP-NC HOME 
O o O CTEPP-OH HOME 


XXX MNCPES 
□ a □ CTEPP-NC DAYCARE 
AAA CTEPP-OH DAYCARE 


DIAZINON 

INDOOR AIR (ng/m3) 


DIAZINON 

OUTDOOR AIR (ng/m3) 




+ + ■+ NHEXAS—AZ 
* * * CTEPP-NC HOME 
O o O CTEPP-OH HOME 


XXX MNCPES 
□ a □ CTEPP-NC DAYCARE 
AAA CTEPP-OH DAYCARE 


+ + + NHEXAS—AZ 
* * * CTEPP-NC HOME 
O O O CTEPP-OH HOME 


XXX MNCPES 
□ □ □ CTEPP-NC DAYCARE 
AAA CTEPP-OH DAYCARE 


CIS-PERMETHRIN 
INDOOR AIR (ng/m3) 


CIS-PERMETHRIN 
OUTDOOR AIR (ng/m3) 




XXX MNCPES 
□ □ □ CTEPP-NC DAYCARE 
AAA CTEPP-OH DAYCARE 


* * * CTEPP-NC HOME 
o o o CTEPP-OH HOME 


XXX MNCPES 
□ □ □ CTEPP-NC DAYCARE 
aaa CTEPP-OH DAYCARE 


* * * CTEPP-NC HOME 
O O O CTEPP-OH HOME 


Figure 3.2 Log probability plots for chlorpyrifos, diazinon, and cw-permethrin measured in large 
observational field studies. Only values above the limit of detection are plotted. 


32 













































TRANS-PERMETHRIN 
INDOOR AIR (ng/m3) 


TRANS-PERMETHRIN 
OUTDOOR AIR (ng/m3) 



XXX MNCPES * * * CTEPP-NC HOME 

D □ □ CTEPP-NC DAYCARE POO CTEPP-OH HOME 
AAA CTEPP-OH DAYCARE 



XXX MNCPES * * * CTEPP-NC HOME 

ODD CTEPP-NC DAYCARE O O O CTEPP-OH HOME 
AAA CTEPP-OH DAYCARE 


TCPY 

INDOOR AIR (ng/m3) 



* * * CTEPP-NC HOME D D D CTEPP-NC DAYCARE 

OOP CTEPP-OH HOME AAA CTEPP-OH DAYCARE 


TCPY 

OUTDOOR AIR (ng/m3) 



* * * CTEPP-NC HOME D D D CTEPP-NC DAYCARE 

OOP CTEPP-OH HOME AAA CTEPP-OH DAYCARE 


IMP IMP 

INDOOR AIR (ng/m3) OUTDOOR AIR (ng/m3) 




Figure 3.3 Log probability plots for fra«.s-permethrin, TCPy, and IMP measured in large 

observational field studies. Only values above the limit of detection are plotted. 


33 














































CHLORPYRIFOS 
INDOOR AIR (ng/m3) 


CHLORPYRIFOS 
OUTDOOR AIR (ng/m3) 


fO 

E 

\ 

o» 

c 


O 

I— 
< 
CL 


UJ 

O 

Z 

o 

o 




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INDOOR AIR (ng/m3) 


DIAZINON 

OUTDOOR AIR (ng/m3) 


to 

E 

\ 

O' 

C 


< 

CL 


O 

z 

o 

o 


10000 - 


1000-1 


100 - 


10 - 


1 7 


0.1 


0.01 - 



B 



n—i—i—i—i—i—i—i i —r 

AZ UN NCHM NCOC OH HU OH DC JAX CHA PET OffC 


10000 

1000 

100 - 

10 — 

1 

o.i 4 
0.01 



B 


n- 1 - 1 - 1 - 1 - 1 - 1 -r~ 

UN NCHM NCDC OH HU OHOC JAX CHA DITC 


CIS-PERMETHRIN 
INDOOR AIR (ng/m3) 


CIS-PERMETHRIN 
OUTDOOR AIR (ng/m3) 


n 

E 

\ 

O' 

c 

z 

O 

< 

CL 


UJ 

o 

z 

o 

o 


10000 - 

1000 - 

100 7 

10 - 

1 - 

0.1 - 

0.01 - 



1-1-1-1-1 I-1 - 

UN NC HU NC DC OH HU OH DC JAX CHA 



Figure 3.4 Indoor and outdoor air concentrations of chlorpyrifos, diazinon, and c/s-permethrin 
measured in selected studies. Legend: AZ = NHEXAS-AZ, MN = MNCPES, NC HM = 
CTEPP-NC Home, NC DC = CTEPP-NC Daycare, OH HM = CTEPP-OH Home, OH DC = 
CTEPP-OH Daycare, CHA = CHAMACOS, TEST = Test House. 


34 
























































































































TRANS-PERMETHRIN 
INDOOR AIR (ng/m3) 


TRANS-PERMETHRIN 
OUTDOOR AIR (ng/m3) 



TCPY 

INDOOR AIR (ng/m3) 


TCPY 

OUTDOOR AIR (ng/m3) 



IMP 

INDOOR AIR (ng/m3) 


IMP 

OUTDOOR AIR (ng/m3) 



10000- 



ro 

E 

1000- 

\ 


o> 


c 

100 

1 ' 

Z 


o 

10- 


< 


Od 


1— 


z 

1 - 

UJ 


o 


z 


o 

0.1 - 

o 

0.01 - 


—I— 

OH HM 


-1 

OH DC 


10000 - 

1000 - 

10Q - 

10 - 

1 - 

0.1 - 

0.01 - 


jL 


OH HU 


OH DC 


Figure 3.5 Indoor and outdoor air concentrations of fraws-permethrin and TCPy measured in 
selected studies. Legend: AZ = NHEXAS-AZ, MN = MNCPES, NC HM = CTEPP-NC Home, 
NC DC = CTEPP-NC Daycare, OH HM = CTEPP-OH Home, OH DC = CTEPP-OH Daycare, 
CHA = CHAMACOS, TEST = Test House. 


35 
















































































Figure 3.6 Log-scale relationships between levels of parent pesticide (ng/m 3 ) and degradate 
(ng/m 3 ) measured in CTEPP. Left Panel: Chlorpyrifos with TCPy. Right Panel: Diazinon with 


IMP. 


36 




3.4 Differences Related to Location 

This section addresses differences in potential for exposure related to geographic region, 
population density (urban vs. rural), and home vs. daycare environment. There is available 
evidence to support all three of these location-related factors as having a discemable impact on 
pesticide exposure. 

The large observational field studies were conducted in several geographical regions. A 
difference in climate impacts the type and density of pests found in the region. Residents of 
areas with mild winter conditions, as exist in the southern United States, may experience 
significant pest control problems throughout the year and may respond with increased pesticide 
usage. The landmark EPA Non-Occupational Pesticide Exposure Study (NOPES) conducted 
during 1986-1988 (Whitmore et al., 1994) reported much higher indoor air concentrations of 
chlorpyrifos and diazinon in Jacksonville, Florida, than in Springfield and Chicopee, 
Massachusetts (purposely selected as high-use and low-use regions, respectively). 

The residents of rural communities may be exposed to pesticides from residential as well as 
agricultural applications. Both spray drift and work-to-home transport are potential pathways of 
exposure to agricultural pesticides, some of which have the same active ingredient as 
formulations used within the home (Curl et al., 2002). Residents of urban areas, on the other 
hand, may experience frequent applications to combat persistent pest control problems arising 
from high population density (Landrigan et al., 1999), may have little control over pesticide 
applications by building management, and may be exposed to pesticides applied in neighboring 
residences. 

Young children spend nearly 20 hours per day indoors (US EPA, 2002). For pre-school age 
children, much of this time is spent in residences or in daycare facilities. According to recent 
estimates, nearly 4 million children under age 6 spend some portion of their day in center-based 
child care, with many children spending a full work day (8-10 hours) in the child care center (US 
CPSC, 1999). Pesticide concentrations in daycare facilities are potentially significant (Wilson et 
al., 2003) and are typically out of the control of the parents. 

• Positive and highly significant associations (p < 0.01) between personal-air exposures 
and indoor air concentrations were observed in MNCPES for both chlorpyrifos and 
diazinon with Spearman correlation coefficients of 0.81 and 0.62, respectively (Table 
3.4). 

• Comparison of the box-and-whisker plots in Figure 3.4 of indoor air concentrations 
measured in homes finds median values were somewhat higher in southern states 
(NHEXAS-AZ and CTEPP-NC) than in northern states (MNCPES and CTEPP-OH). 
However, considerable overlap in the interquartile ranges is evident. Since these studies 
focus on compounds that have been used to control a variety of common insect pests both 
inside and outside of homes (chlorpyrifos was until recently among the most poplar 
residential insecticides for cockroach, flea, ant and termite control), it is not surprising 
that the distributions would overlap across geographical locations. 


37 


• When daycare measurements are included, a geographical difference is less obvious 
(results not shown). Despite recent gains in the adoption of integrated pest management 
policies, many daycare facilities still have regular calendar-based pesticide treatments, 
irrespective of actual demonstrated need. This may have the effect of minimizing 
differences in usage in daycares among geographic regions. 

• CTEPP data (Figure 3.7) suggest that, within each state, indoor air levels in daycares are 
similar to those in homes, particularly for diazinon and permethrin. This demonstrates 
the potential for continued exposure as a child transitions from the home to a daycare. To 
reduce the uncertainty of risk assessments for children, their exposures must be 
considered for all indoor and outdoor environments they occupy, including homes, child 
care centers, and other buildings. Additional information may be required to examine 
exposure potential from schools, restaurants, and other public and private locations where 
pesticides are also applied. 

• Differences between urban and rural air concentrations of chlorpyrifos were observed in 
both MNCPES (Table 3.5) and CTEPP-OH (Table 3.6). The differences reached 
statistical significance only in MNCPES, with higher concentrations in the urban areas. 
Likewise, the detection frequencies for both chlorpyrifos and diazinon in indoor and 
personal air were higher in urban locations (Table 3.5). 

• Across compounds in MNCPES, median levels were consistently higher in urban areas 
than in rural areas. A reasonable explanation may be that urban areas require more 
intensive use of pesticide products to control a range of pests over a wider seasonal span. 
In addition the application may be of more mass of active ingredients in a smaller area, as 
is the case with a liquid termiticide application. While it is not entirely clear why the 
pattern of higher urban levels was not evident in CTEPP-NC, it may be due to a less 
stringent definition of‘"urban” in CTEPP. 

• Air samples collected in low-income homes generally had higher concentrations of 
chlorpyrifos and diazinon than samples collected in medium/high income homes (Table 
3.6), but the difference was only statistically significant for diazinon in NC. 


38 


Table 3.4 Spearman correlations among personal, indoor, and outdoor concentrations of 
chlorpyrifos and diazinon measured in MNCPES 3 . 



Chlorpyrifos 

Diazinon 

Type 

Indoor 

Outdoor 

Indoor 

Outdoor 

Personal 

0.81** 

0.23 

0.62** 

0.67** 

Indoor 

— 

-0.01 

— 

0.28 


a Excerpted from Clayton et al., 2003 
** Statistically significant at the 0.01 level. 


Table 3.5 Urban and rural differences in airborne concentrations of chlorpyrifos and diazinon 
measured in MNCPES. The limit of detection was 0.1 ng/m 3 . 


Sample 

Type 

Chemical 

Location 

N 

Detection 

Frequency 

Median 

Concentration 

(ng/m 3 ) 

Personal 

Chlorpyrifos* 

Urban/Suburban 

40 

98% 

2.2 

Rural 

20 

90% 

1.2 

Diazinon* 

Urban/Suburban 

30 

77% 

0.4 

Rural 

18 

44% 

<0.1 

Indoor 

Chlorpyrifos* 

Urban/Suburban 

57 

96% 

2.2 

Rural 

25 

80% 

0.7 

Diazinon 

Urban/Suburban 

54 

74% 

0.4 

Rural 

21 

52% 

0.1 


* denotes significant (p < 0.05) difference in medians using two-sided Wilcoxon test. 


Table 3.6 Differences in airborne concentrations measured in CTEPP for urban versus rural, low 
versus medium income, and home versus daycare expressed as ratios of geometric means. 
Adapted from Morgan et al., 2004. 




Estimated Ratio of Geometric Means (95% C.I.) 

State 

Chemical 

Urban/Rural 

Low /Mid-High Income 

Home/Daycare 

North 

Chlorpyrifos 

0.94 

(0.50, 1.77) 

1.36 

(0.84,2.21) 

1.78 

(0.81,3.92) 

Carolina 

Diazinon 

0.95 

(0.43,2.11) 

3.59’ 

(1.95,6.61) 

0.82 

(0.30, 2.24) 

Ohio 

Chlorpyrifos 

1.64 

(0.80,3.37) 

1.63 

(0.97, 2.74) 

0.76 

(0.38, 1.52) 

Diazinon 

1.04 

(0.44, 2.49) 

1.67 

(0.89,3.12) 

0.78 

(0.34, 1.80) 


* denotes significance, p < 0.05. 


39 





































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40 


Figure 3.7 The detection frequencies of select pesticides and their metabolites measured from the indoor air (A) and outdoor air (B) of 
homes and daycares in NC and OH, and the mean concentrations of select pesticides and their degradation products measured from 
the indoor air (C) and outdoor air (D) of homes and daycares in NC and OH. 

















































































































3.5 Spatial and Temporal Variability 

Few studies have been designed to measure either the spatial variability of airborne pesticide 
concentrations in a home or the temporal variability following crack-and-crevice pesticide app¬ 
lications (Byrne et al, 1998; Lewis et al, 2001). Recently, the Test House, CPPAES, DIYC, 
and PET studies have provided data on both spatial and temporal variability, as shown in Figure 
3.8. 

• Within-home spatial patterns were investigated in the Test House experiments. 

Following a crack and crevice application of chlorpyrifos (Figure 3.8 and Table 3.7), the 
pesticide was detected in the application room (kitchen), adjacent den, and the farthest 
bedroom from the application. Airborne concentrations in the kitchen peaked at 790 
ng/m 3 , then decreased by approximately 80%, but were still measurable, at 21 days after 
application. A concentration gradient was observed from the kitchen (application area) to 
the den (proximal area) to the master bedroom (distal area). 

• Between-home spatial variability following a pesticide application was investigated in the 
CPPAES and DIYC studies. Indoor air concentrations of chlorpyrifos among the 10 
homes in the CPPAES spanned more than an order of magnitude one day after 
application (Figure 3.8). 

• The highest measured chlorpyrifos indoor air concentrations following crack and crevice 
applications among a subset of 5 CPPAES homes were between days 0 and 2 post applic¬ 
ation (mean = 315 ng/m 3 ), then decreased throughout the 2-week sampling period (mean 
= 172 ng/m3), but were still greater than the pre application levels (mean =18 ng/m 3 ). 

The indoor air concentrations for the remaining CPPAES homes were much lower and 
did not follow the same decay pattern (data not presented, see Hore et al, 2005). 

• Air concentrations of diazinon in the homes of the DIYC study were nearly an order of 
magnitude higher than concentrations of chlorpyrifos in CPPAES, and the decay pattern 
differed dramatically among the three DIYC homes. The difference in airborne diazinon 
concentrations among the three homes was most pronounced 4-5 days after application 
(Figure 3.8), perhaps partially attributable to both the application method employed and 
the amount of active ingredient applied in each home. 

• Following outdoor granular application to lawns in the PET study, indoor air 
concentrations of diazinon generally reached maximal levels by days 1 and 2 post 
application and declined over the duration of the study (Figure 3.8). 

3.6 Factors that Influence Air Concentrations 

Multiple factors influence the concentration of pesticides in air and the potential for inhalation 
exposure. The physico-chemical characteristics of the chemicals applied, the formulation type 
and the frequency of application are believed to be some of the most important of these factors. 
Other factors such as seasonal variation, housing type, pets, occupancy, application location, 
type of surface to which the applications are made, and the rooms where the samples are 
collected may also influence the concentrations measured. Some of these factors have been 


41 


investigated using the data from NERL’s pesticide exposure measurement program. 

• The impact of air exchange rate (AER) on air concentrations is shown in Figure 3.8 for 
the CPPAES data. Indoor air concentrations of chlorpyrifos (immediately following 
application) among the homes spanned more than an order of magnitude. Homes with 
low air exchange rates had higher initial airborne concentrations and a noticeably slower 
reduction of airborne levels. 

• The amount, or mass, of active ingredient applied also clearly affected the concentrations 
measured in CPPAES, with low airborne concentrations observed in three homes 
receiving applications containing only trace amounts of chlorpyrifos (data not presented, 
please see Hore et al., 2005). 

• An empirically derived Application Effective Volume (AEV, applied mass divided by the 
product of air changes per hour and home volume) was applied to the CPPAES data to 
demonstrate the relationship between measured air concentrations, air exchange rate, and 
mass of active ingredient applied. Measured airborne concentration was more 
consistently correlated with AEV than with any of the constituents of AEV (Pearson 
product-moment correlations, data not presented). The association of AEV with airborne 
concentrations measured on the second day after application (Figure 3.9) suggests that 
AEV may serve as an effective surrogate for air concentrations and that constituent 
measures including air exchange rate are important determinants of air concentrations. 

• The geometric mean concentrations of the organochlorine, organophosphate, and 
pyrethroid pesticides measured in indoor air in the absence of a recent application appear 
to be strongly influenced by vapor pressure. Regressing concentrations measured in the 
CTEPP study upon the logged vapor pressures (Figure 3.10) results in nearly equivalent 
R 2 values of 0.69 and 0.70 for homes and daycares, respectively. The importance of 
inhalation as a route of exposure for pesticides is likely to decrease as less volatile 
pesticides are introduced into the market. 

• Results in the US EPA Research Test House comparing total release aerosol to crack and 
crevice applications confirm that the application method is an important factor 
influencing the measured airborne concentration of chlorpyrifos (Table 3.7). The 
application method is also suspected of being a factor responsible for the differences 
observed among homes in the DIYC study. 

• The PET study demonstrates the intrusion of diazinon from an outdoor source. The lawn 
applications resulted in a source of diazinon that contributed to indoor concentrations in 
all homes. Indoor concentrations are likely associated with both the physical 
translocation of particle bound residues and the intrusion of volatilized diazinon from the 
source. The results suggest that lawn applications increase the potential for occupant 
exposure both on the treated lawns and indoors. 

• While some progress has been made in understanding the multitude of factors that 
influence the concentration of pesticides in air and the potential for inhalation exposure, 
additional studies are needed. 


42 


3.7 Summary: Air Concentrations 

As shown in the bulleted lists of observations from these studies, there are a number of factors 
that may impact children’s exposure to pesticides in homes and child care centers. They include 
the following: 

• The physical and chemical characteristics of the pesticides used indoors will have a 
significant impact on exposure via the inhalation route. Airborne concentrations will be 
higher for the more volatile pesticides, such as chlorpyrifos and diazinon (no longer 
registered for indoor use). Use of less volatile alternatives, such as the pyrethroids, will 
likely result in lower airborne concentrations of the active ingredients. 

• The type and method of pesticide application (see Section 2.4) are factors affecting 
exposure. As shown in the Test House experiments, the airborne concentrations are 
higher for foggers than for crack and crevice applications. Past studies have focused on 
crack and crevice and other spray applications, although newer types of applications, 
such as use of gels, may further reduce the translocation of pesticides to areas that may be 
contacted by children. 

• The data from these studies highlight the importance of geographic location on airborne 
concentrations. Frequency of application and total amount of pesticide used may be 
associated with geographic location. 

• The data on spatial variability of pesticide residues within a home are limited. But, data 
from the Test House and other studies show that pesticides are distributed to other 
locations within a building from the point of application and are measurable in air 
samples collected in other rooms. 

• The data also clearly show that there are temporal changes in concentrations following an 
application. These changes are related to air infiltration and air exchange rates in the 
home. The changes are also likely related to degradation processes, but there are few 
studies that have addressed the temporal changes in concentration for different pesticides 
as related specifically to the degradation process. 


43 


Table 3.7 Airborne chlorpyrifos residues collected following a crack and crevice type application 
versus a total release aerosol in the EPA Test House. 


Application 

Type 

Room 

Indoor Air Concentration (ng/m 3 ) 

Pre 

3 hr 

Day 1 a 

Day 2 

Day 3 

Day 7 

Day 14 

Day 21 

Crack and 
Crevice 

Kitchen 

NC b 

NC 

790 

NC 

770 

320 

220 

140 

Den 

3 

NC 

250 

NC 

140 

90 

60 

70 

Bedroom 

NC 

NC 

100 

NC 

0.07 

60 

40 

30 

Total 

Release 

Aerosol 

Living Room 

ND c 

15 

9200 

4100 

2300 

860 

450 

NC 

Den 

ND 

17 

8300 

4000 

2100 

1100 

410 

NC 

Bedroom 

NC 

1.4 

4700 

NC 

NC 

370 

320 

NC 


a Air sampling was initiated immediately following the application and monitored continuously for 24-h. 
b NC indicates the sample was not collected. 
c ND indicates the sample was not detected <0.05 pg/m 3 


44 




















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45 


Figure 3.8 Airborne concentrations (ng/m 3 ) of chlorpyrifos or diazinon measured from indoor air over time in the Test House, PET, 
CPPAES, and DIYC studies. 























































































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Figure 3.9 Association between measured air concentration (ng/m 3 ) and Applied Effective 
Volume (ng/m 3 /h) on the second day after application of chlorpyrifos in CPPAES homes. 



Figure 3.10 Pesticide air concentrations as a function of vapor pressure in CTEPP homes (A) and 
daycares (B). 


46 


























4.0 SURFACE MEASUREMENTS 


4.1 Introduction and Data Availability 

The objectives of measuring pesticide surface residue concentrations and loadings are to describe 
the extent and distribution of concentrations, identity possible sources of indoor contamination, 
evaluate factors that may impact concentrations, and identify elevated concentrations for the 
purposes of intervention. Surface measurements tell us what pesticide residues are present in an 
environment and at what concentrations. With appropriate transfer coefficients and activity data, 
these measurements can be used to estimate dermal and nondietary ingestion exposure. 

Although exposure potential is highest during the first few days following an application, 
pesticide residues introduced into the indoor residential environment may persist for months or 
even years on surfaces or embedded in carpets, where these are protected from sunlight, rain, 
temperature extremes, and microbial action (Lewis et al., 1994). Surface residues may 
contribute to the exposure of household occupants through multiple routes: dermal absorption, 
inhalation of resuspended particles, nondietary ingestion of residues adhering to mouthed objects 
and skin, and dietary ingestion resulting from children’s unique handling of food (Butte and 
Heinzow, 2002). Oral ingestion and dermal absorption of surface residues may be major routes 
of exposure for infants and toddlers who spend much of their time on the floor, explore their 
world through mouthing, experience frequent hand-to-mouth and object-to-mouth contacts, and 
who may have pica tendencies (Butte and Heinzow, 2002; Cohen Hubal et al., 2000a, b; 

Freeman et al., 2004; Lewis et al., 1994; Tulve et al., 2002). Ingestion of soil is also a special 
concern for young children, who may ingest up to 10 times more soil than adults on a per 
kilogram body weight basis (LaGoy, 1987). 

Several surface sampling methods exist including deposition coupons, Octadecyl (Cl 8) surface 
press sampler (EL Sampler), Lioy-Weisel-Wainman (LWW) sampler, vacuum, drag bar, 
Califomia-roller, PUF roller, and surface wipes. These methods are generally classified by the 
degree to which they remove residues from surfaces: total available residue, transferable residue, 
and dust (Lewis, 2001). Total available residue methods attempt to measure the total amount of 
contaminant on a surface (often with the aid of isopropanol as a solvent), transferable residue 
methods are intended to represent the amount that is transferred as a result of contact with the 
contaminated surface, and dust collection methods use a vacuum to collect dust-borne residue on 
surfaces and from carpet. Transferable residues are also referred to as dislodgeable residues. All 
studies discussed in this chapter employed more than one sampling method for surface measure¬ 
ments. Table 4.1 lists the studies that collected surface measurements along with the type of 
measurement taken. Limits of detection for each chemical by study and method are listed in 
Table 4.2. 

Several variables may influence measured dust concentrations or surface loadings of pesticide 
residues. These variables include the collection method itself, surface type, compound physico¬ 
chemical characteristics, application method, application frequency, sampling locations, 
participant activities, and analytical capabilities. This chapter examines how these factors may 
have affected the surface residue measurements in the children’s exposure measurement 
program, the implications for interpreting the data, and the consequences for exposure estimates. 


47 


Table 4.1 Studies and sample collection methods for surface measurements. 


Study 

Dust 

(ng/g) 

Dust Load 
(ng/cm 2 ) 

Soil 

(ng/g) 

Total Surface Load 
(ng/cm 2 ) 

Transferable Residues 
(ng/cm 2 ) 

NHEXAS-AZ 

V 


V 

— 

Wipes (water) 

MNCPES 




LWW 

C18 Press 

CTEPP 

V 

V 

S 

— 

Wipes (2 mL IP A), 

PUF Roller 

CCC 

— 

— 


Wipes (20 mL IP A) 

Cl8 Press 

JAX 

— 

— 

— 

Wipes (20 mL BP A) 

Cl8 Press 

CHAMACOS 




Wipes (20 mL IP A) 

Cl8 Press 

CPPAES 

— 

— 

— 

Deposition Coupons, 
LWW 

— 

Test House 

— 

— 

— 

Deposition Coupons, 
Wipes (10 mL IP A) 

PUF Roller 

Cl8 Press 

PET 

V 

— 



PUF Roller 

DIYC 

— 

— 

— 

Wipes (20 mL IP A) 

PUF Roller 

Daycare 

— 

— 

— 

Wipes (20 mL BP A) 

PUF Roller, 

Cl8 Press 


—, matrix not sampled 
LWW, Lioy-Weisel-Wainman sampler 
Cl8, 3M Empore™ Octadecyl (Cl8) filters 
PUF, Polyurethane foam 


48 





















Table 4.2 Limits of detection (ng/g or ng/cm 2 ) for surface measurements by study, method, and 
compound. 


Study 

Method 

Chlor- 

pyrifos 

Diaz- 

inon 

c-Per- 

methrin 

f-Per- 

methrin 

Cyflu- 

thrin 

Cyper- 

methrin 

Esfen- 

valerate 

TCPy 

IMP 

Soil (ng/g) 

MNCPES 

Soil 

10 

10 

10 

10 

— 

— 

— 

— 

— 

CTEPP 

Soil 

0.5 

0.5 

0.5 

0.5 

5 

— 

— 

0.2 

0.2 

CCC 

Soil 

5 

2 

5 

5 

6 

6 

— 

— 

— 

PET 

Soil 

— 

60 

. — 

— 

-- 

— 

— 

— 

— 

Dust (ng/cm 2 or ng/g) 

NHEXAS-AZ 

Dust (ng/cm 2 ) 

0.002 

0.002 

— 

— 

— 

— 

— 

— 

— 

CTEPP 

Dust (ng/cm 2 ) 

0.0003 

0.0003 

0.0003 

0.0003 

0.0030 

— 

— 

0.0003 

-- 

NHEXAS-AZ 

Dust (ng/g) 

4 

18 

— 

— 

— 

— 

— 

— 

— 

CTEPP 

Dust (ng/g) 

2 

2 

2 

2 

10 

— 

— 

2 

2 

CHAMACOS 

Dust (ng/g) 

1 

1 

1 

1 

100 

— 

— 

— 

— 

PET 

Dust (ng/g) 

— 

60 

— 

— 

— 

— 

— 

— 

— 

Total Available Residue (ng/cm 2 ) 

NHEXAS-AZ 

IPA Wipe 

0.070 

2.00 

— 

— 

— 

— 

-- 

— 

— 

MNCPES 

LWW 

1.200 

3.50 

— 

— 

— 

— 

— 

— 

— 

CCC 

IPA Wipe 

0.005 

0.002 

0.005 

0.005 

0.006 

0.006 

— 

— 

— 

JAX 

IPA Wipe 

0.005 

0.002 

0.005 

0.005 

0.006 

0.006 

0.008 

— 

— 

CHAMACOS 

IPA Wipe 

0.005 

0.005 

0.005 

0. 002 

— 

— 

— 

— 

— 

CPPAES 

IPA Wipe 

0.001 

— 

— 

— 

— 

— 

— 

— 

— 

CPPAES 

LWW 

0.030 

— 

— 

— 

— 

-- 

— 

— 

— 

CPPAES 

Dep Coup 

0.010 

— 

— 

— 

— 

— 

— 

— 

— 

TESTHOUSE 

IPA Wipe 

0.001 

— 

— 

— 

-- 

— 

— 

— 

— 

TESTHOUSE 

Dep Coup 

0.010 

— 

— 

— 

— 

— 

— 

— 

— 

DIYC 

EPA Wipe 

— 

0.300 

— 

— 

— 

— 

-- 

— 

— 

DAYCARE 

IPA Wipe 

— 

— 

— 

— 

— 

— 

0.400 

— 

— 

Transferable Residue (ng/cm 2 ) 

MNCPES 

Cl8 Press 

0.330 

0.140 

— 

— 

— 

— 

— 

— 

— 

CTEPP 

IPA Wipe 

0.0007 

0.0007 

0.0007 

0.0007 

0.007 

— 

— 

0.0007 

0.0007 

CTEPP 

PUF 

0.0004 

0.0004 

0.0004 

0.0004 

0.004 

— 

— 

0.0004 

0.0004 

TESTHOUSE 

C18 Press 

0.030 

— 

— 

— 

— 

— 

— 

— 

— 

TESTHOUSE 

PUF 

0.001 

— 

— 

— 

— 

— 

-- 

-- 

— 

PET 

PUF 

— 

0.030 

— 

-- 

— 

— 

— 

— 

— 

DIYC 

Cl 8 Press 

— 

1.200 

— 

— 

— 

-- 

— 

— 

— 


—, analyte not measured 


49 
























































































4.2 Dust and Soil Measurements 

Dust is considered a repository of environmental pollutants that have accumulated indoors from 
both internal and external sources. Dust collected by vacuum is usually sieved to retain a 
particular size fraction for analysis, which may have important implications since pesticide 
concentrations are inversely related to particle size (Lewis et al, 1999). Measurements in dust 
may be reported as concentrations (mass residue per unit weight of dust, ng/g) or as loadings 
(mass residue per unit area sampled, ng/cm 2 ). There is a lack of consensus on which of these 
metrics is more relevant to human exposure to pesticides; however, lead studies have suggested 
that lead loading correlates better with children's blood lead levels than does lead concentration 
(Lanphear, 1995). 

Pesticides were measured in dust samples from the NHEXAS-AZ, CTEPP, CHAMACOS and 
PET studies. The CTEPP, CHAMACOS, and PET studies used the High Volume Small Surface 
Sampler (HVS3), whereas NHEXAS-AZ used a modified commercially available vacuum for 
ease of sample collection. The HVS3 was developed for the EPA and efficiently collects carpet- 
embedded dust retaining the associated pesticides (Roberts et al, 1991; Lewis et al, 1994). The 
HVS3 is a high-powered vacuum cleaner equipped with a nozzle that can be adjusted to a 
specific static pressure and air flow rate. A cyclone removes particles >5 (im from the air stream 
for collection in a catch bottle. Use of this sampler is limited to floors or other large flat surfaces 
(Roberts et al, 1991; Ness, 1994; Lewis et al, 1994). The ASTM (American Society for Testing 
and Materials) method for the collection of carpet-embedded dust requires an apparatus with the 
specifications of the HVS3 (ASTM, 1993). Pesticide concentrations in soil were measured in the 
same studies and results have been included in this chapter to allow comparisons between indoor 
and outdoor exposure pathways for the same children. 

Pesticide Presence in Dust and Soil 

Detection limits are listed in Table 4.2. Detection frequencies are presented in Figure 4.1 for soil 
samples and Figure 4.2 for dust samples. Concentrations of pesticides in soil and dust samples at 
the median and 95 th percentile are listed in Table 4.3 (complete summary statistics are listed in 
Tables A.8 through A. 19 in Appendix A). 

• With the exception of cyfluthrin (for which analytical difficulties produced a higher 
detection limit), dust samples had high detection frequencies (>95%) in CTEPP and 
CHAMACOS. Detection frequencies were lower in NHEXAS-AZ due to higher 
detection limits. 

• The high detection frequencies of pesticides observed in dust across studies is consistent 
with dust being a repository of contaminants. 

• Detection frequencies for soil samples, on the other hand, were generally low (Figure 
4.1). The high detection frequency of diazinon in PET study soil was due to direct lawn 
applications of the pesticide prior to sample collection. 

• Pesticide concentrations were much lower in soil samples than in dust samples. In 
general, soil levels at the 95 th percentile were a factor of 10 to 100 times lower than dust 
levels at the same percentile. This result suggests that in the absence of outdoor turf 
treatments, ingestion of soil may not be an important exposure pathway for these 


50 


pesticides, with the possible exception of children exhibiting pica behavior. 

Concentrations in Dust and Soil: Summary Findings 

Lognormal probability plots that graphically depict pesticide concentrations in soil from large 
observational field studies are presented in Figure 4.3. Plots that depict pesticide concentrations 
and loadings in dust are given in Figures 4.4 and 4.5. Box-and-whisker plots comparing 
pesticide concentrations and loadings in dust across all studies are given in Figures 4.6 and 4.7. 

• The upper tails of the soil concentration distributions tend to be in the same range as the 
lower tails of the dust concentration distributions (Figures 4.3-4.5). For example, the 95 th 
percentile for both chlorpyrifos and diazinon in soil is approximately 10 ng/g, and the 5 th 
percentile for both of these compounds in dust is also near 10 ng/g. 

• Among the pesticides measured in soil, cyfluthrin stands out for its high values at the 
95 th percentile (Table 4.3). Due to the low detection frequencies, no additional analysis 
was conducted with the soil data. 

• Comparisons of concentrations in dust across studies (Figures 4.4-4.5) show permethrin 
(a pyrethroid) to be about an order of magnitude higher than chlorpyrifos and diazinon 
(both organophosphates). 

• Overall, diazinon concentrations are lower than all other pesticides reported in dust, as 
illustrated in the box-and-whisker plots (Figures 4.6-4.7). 

• High loadings of diazinon in indoor house dust following the lawn treatment in the PET 
study suggest translocation into the house by the occupants and their pets. 

• The concentration ranking among the compounds in dust is the opposite of that found in 
air where the more volatile pesticides showed the higher concentrations. The less volatile 
pyrethroid pesticides tend to partition to the dust and may degrade more slowly, allowing 
accumulation over time from repeated applications. These results point to the importance 
of dust as a primary residential exposure medium for the less volatile pesticides. In 
addition, the exposure factors that are important for other nonvolatile contaminants such 
as lead (Melnyk et al., 2000) may also be important for the less volatile pesticides. 

• In general, the lognormal plots (Figures 4.4-4.5) indicate that differences between study 
populations are more apparent with dust loadings than with dust concentrations. 

• In CTEPP, pesticide loadings in surface dust (ng/cm 2 ) were higher in daycare centers 
(DC) than in homes (HM) (Figures 4.6-4.7). This appears to be a function of the amount 
of surface dust present, as the pesticide concentrations in the dust do not differ by much 
(Figures 4.6-4.7). Studies with lead have suggested that loading has a greater impact than 
concentration on intake, and the same may or may not be true for pesticides. 

• Concentrations of chlorpyrifos in dust (ng/g) are similar across studies (Figure 4.4) 
suggesting that the usage of chlorpyrifos did not change significantly from the timeframe 
of the NHEXAS-AZ study (1995-1997) to the CTEPP study (2000-2001). 

• As with the other surface measurement methods, cis- and /raws-permethrin have similar 

concentration profiles in dust samples. 


51 


fL 

Table 4.3 Median and 95 percentile values for soil (ng/g) and dust (ng/cm 2 and ng/g) measurements by study. 


IMP 

P95 

SOIL 

j 

1 

1 

1 

1 

VZ 

1.4 

1 

1 

1 

1 

DUST (Loadings) 

1 

1 

! 

! 

0.046 

0.072 

1 

1 


1 

1 

1 

! 


310 

! 

1 

l 

P50 

1 

l 

1 

l 

1 

1 

CN 

O 

V 

<0.2 

1 

I 

1 

1 

1 

l 

s 

i 

i 

o 

o 

d 

o 

p 

d 

! 


1 

1 

1 

1 

1 

1 


r- 

i 

i 

1 

1 

TCPy 

P95 

I 

l 

11.0 

CN 

8.9 

6.3 

l 

1 

1 

1 

l 

1 

0.37 

0.37 

0.16 

ovo 

! 

1 

1 

1100 

ooe 

820 

500 

i 

i 

l 

1 

P50 

1 

l 

0.6 

<0.2 

0.7 

0.6 

' 

1 

1 

j 

0.008 

0.020 

N" 

O 

O 

d 

0.024 

i 

i 

! 

96 

63 


67 

i 

i 

1 

l 

Cyfluthrin 

P95 

1 

l 

32.0 

42.0 

64.0 

42.0 

8.6 

1 

1 

l 

0.16 

0.60 

0.25 

on 

j 

i 

1700 

1500 

1300 

890 

303.6 

l 

1 

P50 

I 

i 

o 

in 

V 

p 

in 

V 

o 

in 

V 

<5.0 

<6.0 

1 

1 

1 

i 

<0.003 

<0.003 

oo 

o 

d 

o 

'T 

d 

i 

i 

r~ 

79 

200 

350 

<50 

! 

/-Permethrin 

P95 

| 

p 

od 

2.2 

r—H 

c-i 

<0.5 

CN 

1 

1 

I 

i 

4.40 

6.30 

3.90 

4.70 

i 

i 

■ 

i 

o 

o 

o 

ON 

12000 

o 

o 

CN 

On 

3400 

15000 

i 

i 

P50 

l 

I 

in 

d 

V 

<n 

d 

V 

<0.5 

<0.5 

<5.0 

1 

1 

l 

l 

0.09 

0.41 

0.03 

0.31 

i 

i 

! 

630 

760 

340 

480 

40 

i 

i 

c-Permethrin 

P95 

1 

I 

13.0 

2.6 

2.7 

in 

o 

V 

8.6 

1 

1 

! 

4.90 

5.50 

3.80 

o 

oo 

It 

1 

■ 

i 

21000 

10400 

7600 

o 

o 

oo 

m 

2900 

i 

i 

P50 

1 

l 

<0.5 

<0.5 

•n 

d 

V 

<0.5 

o 

in 

V 

1 

1 

! 

oro 

0.69 

in 

o 

d 

0.27 

i 

i 

i 

i 

o 

o 

oo 

890 

470 

069 

150 

i 

i 

Diazinon 

P95 

<10.0 

4.2 

in 

d 

V 

4.7 

C< 

22.0 

o 

o 

o 

o 

n 

oo 

d 

ZVO 

9.90 

0.31 

On 

d 

68 

o 

o 

o 

OO 

390 

0069 

1700 

1600 

820 

o 

o 

o 

o 

m 

P50 

<10.0 

«n 

d 

V 

<0.5 

m 

d 

V 

in 

d 

V 

<2.0 

22000 

0.002 

0.002 

0.026 

0.002 

0.022 

0.350 

150 

oo 

47 

20 

38 

f—H 

CN 

3100 

Chlorpyrifos 

P95 

o 

d 

t—H 

V 

17.0 

oo 

d 

14.0 

6.2 

27.0 

1 

l 

2.80 

ZVO 

1.30 

0.35 

0.89 

i 

l 


o 

o 

o 

o 

CN 

1200 

920 

1400 

1100 

1200 

1 

P50 

O 

d 

t—H 

V 

<n 

d 

V 

<0.5 

<0.5 

«n 

d 

V 

p 

«n 

V 

l 

1 

t'' 

o 

o 

d 

0.009 

0.066 

0.006 

0.046 

i 

1 


140 

130 

140 

52 

o 

oo 

T—H 

49 

I 

l 

Units 

DO 

~Sl) 

g 

00 

'ob 

g 

00 

'So 

c 

00 

'£3b 

g 

00 

'So 

G 

DO 

'So 

e 

DO 

'SO 

a 

CN 

6 

o 

'SO 

g 

(N 

a 

'SO 

a 

CN 

a 

a 

CN 

a 

o 

~Sb 

G 

a 

G 

a 

72) 

G 

C/5 

G 

O 

• H 
*-* 

S' 3 

DD 

'Sb 

G 

G 

DO 

'Sh 

G 

■sS 

G 

■Sb 

G 

0J) 

'S3) 

G 

DO 

I 3 


MNCPES 

U 

% 

Oh 

Oh 

W 

H 

U 

CTEPP-NC d 

CTEPP-OH h 

CTEPP-OH d 

ccc 

PET 

NHEXAS-AZ 

CTEPP-NC h 

CTEPP-NC d 

CTEPP-OH h 

CTEPP-OH d 

PET 

.b 

G 

0) 

o 

G 

O 

O 

H 

00 

D 

Q 

NHEXAS-AZ 

CTEPP-NC h 

CTEPP-NC d 

CTEPP-OH h 

CTEPP-OH d 

CHAMACOS 

PET 


52 


CTEPP: h = home, d = daycare 
analyte not measured 


























































































Detection Frequency: Soil 



■■MNCPES EH33 CTEPP-NC CHICTEPP-OH CH1CCC I IPFT 


Figure 4.1 Detection frequencies of pesticides and degradates in soil. 


Detection Frequency: Dust 


>» 

o 

c 

a> 

3 

IT 

a> 


c 

o 

'■3 

0) 

a> 

a 



■ 

Chlorpyrifos 



I I » 

c-Perm t-Penm Cyfluthrin 


Wm NHEXAS-AZ S3 CTEPP-NC □ CTEPP-OH CHAMACOS B PET 



Figure 4.2 Detection frequencies of pesticides and degradates in dust. 


53 



















































































CHLORPYRIFOS 
SOIL CONCENTRATION (ng/g) 


DIAZINON 

SOIL CONCENTRATION (ng/g) 



XXX MNCPES * * * CTEPP-NC HOME 

□ O □ CTEPP-NC DAYCARE O O O CTEPP-OH HOME 

AAA CTEPP-OH DAYCARE • • • CCC 



. 1 . 2.5 1 2 5 10 2050 50 7080 90 95 99 99.9 

Percent 


XXX MNCPES * * * CTEPP-NC HOME 

□ O □ CTEPP-NC DAYCARE . « O O CTEPP-OH HOME 

AAA CTEPP-OH DAYCARE • • • CCC 


CIS-PERMETHRIN 
SOIL CONCENTRATION (ng/g) 


TRANS-PERMETHRIN 
SOIL CONCENTRATION (ng/g) 



. 1 . 2.5 1 2 5 10 2050 50 7080 90 95 99 99.9 

Percent 


* * * CTEPP-NC HOME □ □ □ CTEPP-NC DAYCARE 

o o o CTEPP-OH HOME AAA CTEPP-OH DAYCARE 

• • • CCC 



* * * CTEPP-NC HOME □ Q a CTEPP-NC DAYCARE 

A O O CTEPP-OH HOME AAA CTEPP-OH DAYCARE 

• • • CCC 


CYFLUTHRIN TCPY 

SOIL CONCENTRATION (ng/g) SOIL CONCENTRATION (ng/g) 




* * * CTEPP-NC HOME □ □ □ CTEPP-NC DAYCARE 

o O CTEPP-OH HOME AAA CTEPP-OH DAYCARE * * * CTEPP-NC HOME □ □ □ CTEPP-NC DAYCARF 

• • • CCC o o o CTEPP-OH HOME AAA CTEPP-OH DAYCARE 


Figure 4.3 Lognormal probability plots of soil concentrations (ng/g) for chlorpyrifos, diazinon, 
c/s-permethrin, /rafts-permethrin, cyfluthrin, and TCPy. 


54 






































CHLORPYRIFOS 
OUST CONCENTRATION (ng/g) 


CHLORPYRIFOS 
DUST LOADING (ng/cm2) 




.1 .5 1 2 5 10 2030 50 7080 90 95 99 99.9 

Percent 

+ + + NHEXAS-A2 * * * CTEPP-NC HOME 

□ an CTEPP-NC DAYCARE P P P CTEPP-OH HOME 
AAA CTEPP-OH DAYCARE 


.1.2 .5 1 2 5 10 20 3040 6070 80 90 95 99 99.9 

Percent 


+ + + NHEXAS-AZ 
□ □ □ CTEPP-NC DAYCARE 
AAA CTEPP-OH DAYCARE 


* * * CTEPP-NC HOME 
o O O CTEPP-OH HOME 


DIAZINON 

DUST CONCENTRATION (ng/g) 


DIAZINON 

DUST LOADING (ng/cm2) 




+ + + NHEXAS-AZ 
□ □ □ CTEPP-NC DAYCARE 
AAA CTEPP-OH DAYCARE 


* * * CTEPP-NC HOME 
P o o CTEPP-OH HOME 


.1.2 .5 1 2 5 10 20 3040 6070 80 90 95 

Percent 


99 99.9 


+ + + NHEXAS-AZ 
□ □ □ CTEPP-NC DAYCARE 
aaa CTEPP-OH DAYCARE 


* * * CTEPP-NC HOME 
POP CTEPP-OH HOME 


CIS—PERM ETHRIN 
DUST CONCENTRATION (ng/g) 


CIS-PERMETHRIN 
DUST LOADING (ng/cm2) 




Percent 


* * * CTEPP-NC HOME 
P P P CTEPP-OH HOME 


□ □ O CTEPP-NC DAYCARE 
AAA CTEPP-OH DAYCARE 


+ * * CTEPP-NC HOME 
P P P CTEPP-OH HOME 


□ □ □ CTEPP-NC DAYCARE 
AAA CTEPP-OH DAYCARE 


Figure 4.4 Lognormal probability plots of dust concentrations (ng/g) and loadings (ng/cm 2 ) for 
chlorpyrifos, diazinon, and c/s-permethrin. 


55 


























































TRANS-PERMETHRIN 
DUST CONCENTRATION (ng/g) 


TRANS-PERMETHRIN 
DUST LOADING (ng/cm2) 


1000000 

1OOOOO 

lOOOO 

1000 
100 

10 
1 
.1 

.1 .51 2 5 10 2050 50 7080 90 95 99 99.9 .1.2.5 1 2 5 10 20 5040 607080 90 95 99 99.9 

Percent Percent 




* * * CTEPP-NC HOME 
POO CTEPP-OH HOME 


D □ □ CTEPP-NC DAYCARE 
AAA CTEPP-OH DAYCARE 


* * * CTEPP-NC HOME 
O O O CTEPP-OH HOME 


□ □ □ CTEPP-NC DAYCARE 
AAA CTEPP-OH DAYCARE 


CYFLUTHRIN 

DUST CONCENTRATION (ng/g) 


CYFLUTHRIN 

DUST LOADING (ng/cm2) 



* * * CTEPP-NC HOME □ □ □ CTEPP-NC DAYCARE * * * CTEPP-NC HOME □ □ □ CTEPP-NC DAYCARE 

O O o CTEPP-OH HOME AAA CTEPP-OH DAYCARE o o o CTEPP-OH HOME AAA CTEPP-OH DAYCARE 


TCPY 

DUST CONCENTRATION (ng/g) 


TCPY 

DUST LOADING (ng/cm2) 


1000000 - 

1 III 1 

1 III 1 

100000 • 

1 III 1 

1 III 1 

1 III 1 

10000 ■ 

1 III 1 


1 ^ * 

1000 ; 


100 - 

\ J 

10 - 





* * ^ 

1 1 

1 III 1 

1 III 1 

.1 • 

1 III 1 

t— i- 1 —i—i-1- 1 -r-^-i—i—1—i—P*n- 1 -1- 1 -r 


.1 .5 1 2 5 10 2050 50 7080 90 95 99 99.9 

Percent 



* * 4= CTEPP-NC HOME 
O O O CTEPP-OH HOME 


□ □ □ CTEPP-NC DAYCARE 
AAA CTEPP-OH DAYCARE 


* * * CTEPP-NC HOME 
O <> O CTEPP-OH HOME 


□ an CTEPP-NC DAYCARE 
AAA CTEPP-OH DAYCARE 


Figure 4.5 Lognormal probability plots of dust concentrations (ng/g) and loadings (ng/cm 2 ) 
/ra/w-permethrin, cyfluthrin, and TCPy. 


56 
























































CONCENTRATION (ng/g) CONCENTRATION (ng/g) CONCENTRATION (ng/g) 


CHLORPYRIFOS 
DUST CONCENTRATION (ng/g) 


CHLORPYRIFOS 
DUST LOADING (ng/cm2) 



<N 

E 

o 

\ 

o> 

o 

z 

Q 

< 

o 


100 

10-y 

i 

o.i 

0.01 
0.001 -| 
0.0001 1 
0.00001 - 



X ER 


AZ NC HM NC DC OH HM OH DC CHA 


AZ 


—i-1-1-1- r~ 

NC HM NC DC OH HM OH DC CHA 


DIAZINON 

DUST CONCENTRATION (ng/g) 


DIAZINON 

DUST LOADING (ng/cm2) 


1000000 

100000 

10000 

1000 

100 

10 

1 

0.1 T 



X 


CN 

£ 

o 

\ 

cn 

c 

V_/ 

o 

z 

o 

< 

o 


100 , 

10 
11 
0.1 1 
0.01 - 
0.001 
0.0001 

0.00001 - 


n-1-1-1-1-1- r ~ 

AZ NC HM NC DC OH HM OH DC CHA PET 



1 - 1 - 1 - 1 - 1 - 1 - 1 

AZ NC HM NC DC OH HM OH DC CHA PET 


CIS-PERMETHRIN 
DUST CONCENTRATION (ng/g) 


CIS-PERMETHRIN 
DUST LOADING (ng/cm2) 


10000001 
100000 - 
10000 , 
1000 

100 

10 

1 

0.1 



CM 

E 

o 

\ 

cn 

c 

C3 

Z 

o 

< 

o 


100 
10i 
1, 

0.1 , 
0.01 1 
0.001 

0.0001 

o.ooooi H 



—I I i r i 

NC HM NC DC OH HM OH DC CHA 


—i-1-1-1- r~ 

NC HM NC DC OH HM OH DC CHA 


Figure 4.6 Box-and-whisker plots of dust concentrations (ng/g) and loadings (ng/cm 2 ) for 
chlorpyrifos, diazinon, and c/s-permethrin. 


57 






























































































































































CONCENTRATION (ng/g) CONCENTRATION (ng/g) CONCENTRATION (ng/g) 


TRANS-PERMETHRIN 
DUST CONCENTRATION (ng/g) 


TRANS-PERMETHRIN 
DUST LOADING (ng/cm2) 



100 


CN 

E 


o 

\ 

cn 

c 


,0 1 

1 -! 

0.1 -i 


u 0.01 - 

Q 

< 0.001 - 


0.0001 - 




0.00001 - 


T 


T 


T 


NC HM NC DC OH HM OH DC CHA 


CYFLUTHRIN 

DUST CONCENTRATION (ng/g) 


CYFLUTHRIN 

DUST LOADING (ng/cm2) 



CN 

E 

o 

\ 

cn 

c 

N-/ 

o 

z 

Q 

< 

o 


100 1 
10 1 
11 
0.1 -j 
0.01 i 
0.001 

0.0001 - 

0.00001 - 



I I - I ~T“ T - 

NC HM NC DC OH HM OH DC CHA 


TCPY 

DUST CONCENTRATION (ng/g) 


TCPY 

DUST LOADING (ng/cm2) 




100 n 


10 -i 

/— V 


CN 

1 ■; 

E 

O 


\ 


cn 

0.1 

c 


>— • 


o 

0.01 -! 

z 

Cl 


< 

o 

0.001 - 

_J 

0.0001 1 


0.00001 - 



I-1-1-f— 

NC HM NC DC OH HM OH DC 


Figure 4.7 Box-and-whisker plots of dust concentrations (ng/g) and loadings (ng/cm 2 ) for trans- 
permethrin, cyfluthrin, and TCPy. 


58 









































































































4.3 Total Available Residue Measurements 


Total available residue methods are intended to measure the total amount of contaminant on a 
surface. These methods involve either a solvent-assisted mechanical (wiping) action or the 
stationary capture of descending airborne droplets and particles. Total available residue loadings 
were measured in: 

• NHEXAS-AZ using the LWW sampler, 

• MNCPES using the LWW sampler, 

• CCC from the floors and other surfaces (e.g., counters, desktops) using surface wipes, 

• JAX from the floor in the application area using surface wipes, 

• CHAMOCOS using surface wipes, 

• CPPAES using the LWW and deposition coupons, 

• Test House using deposition coupons and surface wipes, 

• DIYC using surface wipes, and 

• Daycare using surface wipes. 

The Lioy-Weisel-Wainman (LWW) sampler (Patent #RWJ-91-28) was developed to 
quantitatively measure dust on smooth surfaces and has been validated in laboratory and field 
tests (Lioy et al., 1993; Freeman et al., 1996). The LWW sampler achieves quantitative wipe 
collection using a movable constant pressure block within a template marking a specific area of 
100 cm 2 . Octadecyl-bonded (Cl8) disks that have been immersed in isopropyl alcohol are 
attached to a silicon rubber pad on the block. More details about this sampler can be found in 
Gurunathan et al. (1998) and Hore (2003). 

Surface wipes are typically surgical dressing sponges wetted with isopropyl alcohol (IPA). The 
sponge is wiped multi-directionally through a defined area in an S-shaped configuration. Floor 
locations where young children may spend the most amount of time are usually selected. 

Residue loadings on irregularly shaped objects such as toys that are frequently handled by 
children (for estimating indirect ingestion exposures) are also measured using the wipe method. 

Deposition coupons are used to estimate surface loadings of airborne and dust-bound residues 
that “settle out” of the air following an application (Ness, 1994). These consist of a sorptive 
material (e.g., cotton, sponge, rayon) with a non-sorptive backing (aluminum foil) (Stout and 
Mason, 2003) and are placed in locations where the coupons will not be disturbed. Coupons may 
be repeatedly collected and replaced (interval) or collected only at the end of the sampling event 
(cumulative). Both interval and cumulative types were collected in CPPAES, whereas only 
interval deposition coupons were used in the Test House. 


59 




Pesticide Presence in Total Available Residues 

Limits of detection for each chemical by study are given above in Table 4.2. Detection 
frequencies are given in Figure 4.8. 

• The limits of detection varied widely among studies, but are similar within a study for 
both organophosphate and pyrethroid pesticides. 

• Following dust methods, total available residue methods have the lowest limits for 
detection. 

• Detection frequencies were slightly higher for the organophosphate pesticides in two of 
the three studies where both OP and pyrethroid pesticides were measured. 

• Detection frequencies were higher in the smaller, focused studies than in the survey 
studies due to timing of the measurements with respect to recent applications. 


Total Available Residues: Summary Findings 

Surface loadings for the median and 95 percentile are listed in Table 4.4 for all of the pesticides 
that were detected across studies (complete summary statistics are listed in Tables A.20 through 
A.24 in Appendix A). Lognormal probability plots are presented in Figure 4.9 for the most 
frequently detected pesticides which include chlorpyrifos, diazinon, cis- and ^raws-permethrin, 
cyfluthrin, and cypermethrin. The MNCPES data are not included because of the comparatively 
high detection limit and low detection frequencies. Box and whisker plots that graphically depict 
the total available residue loading results from all studies are given in Figure 4.10. 

• In wipe samples, permethrin levels reported at the 95 th percentile were approximately an 
order of magnitude higher than chlorpyrifos and diazinon levels at the 95 th percentile 
(Table 4.4). 

• Levels of diazinon and esfenvalerate reported at the 95 th percentile were at least an order 
of magnitude higher in studies with a known application (DIYC, Daycare) than in the 
survey studies (CCC, JAX-Screening). 

• The lognormal probability plots (Figure 4.9) show that loadings of all frequently detected 
pesticides are substantially higher in the JAX screening wipe samples than in the CCC 
and CHAMACOS wipe samples. 

• The total available residue distributions (Figure 4.9) of chlorpyrifos and cis- and trans- 
permethrin are relatively similar to each other within a specific large observational field 
study. 

• Cypermethrin loadings tend to be the highest and diazinon loadings tend to be the lowest 
(Figure 4.9) of the pesticides of interest in the large observational field studies. 

• The boxplots (Figure 4.10) reveal that chlorpyrifos, diazinon, and esfenvalerate loadings 
are substantially higher in those studies with a known application (CPPAES, Test House, 
DIYC, and Daycare). 


60 


• Low cyfluthrin loadings in wipe samples in Figure 4.9 (substantially lower than all other 
pesticide residues) suggest that cyfluthrin may not have been routinely used for pest 
treatment. 

• MNCPES and CPPAES are the only studies that employed the LWW. The chlorpyrifos 
loadings measured in CPPAES were significantly higher (ANOVA, p=0.002, test results 
not presented) due to known pesticide applications coinciding with the sampling period. 

• Although the MNCPES measurements did not coincide with a pesticide application, 62% 
of the LWW samples had detectable levels of chlorpyrifos, suggesting that chlorpyrifos 
remains on residential surfaces for a long period of time. It is unclear, however, how 
much of this is readily available for transfer and how much is freed from the pores and/or 
body material of the surfaces by the mechanical and solvent action of the LWW sampler. 

• Mean post-application deposition coupon levels were significantly higher in the Test 
House than in CPPAES (ANOVA, p<0.0001, test results not presented). Factors 
responsible may include the following: three CPPAES homes received applications with 
only trace chlorpyrifos concentrations; the application performed in the Test House may 
have been more thorough than applications in the CPPAES homes; the Test House may 
have had a higher application of active ingredient per effective volume of the home (see 
Section 3.6), and some of the CPPAES occupants reported cleaning their homes and/or 
intentionally increasing ventilation after application, thereby reducing the amount of 
chlorpyrifos available for movement and capture on a deposition coupon. 

• In studies ( e.g CPPAES) where surface wipe samples were collected both pre- and post¬ 
application of a semi-volatile pesticide such as chlorpyrifos, the post-application 
pesticide loadings were higher than the pre-application values, including on surfaces that 
did not receive a direct application. This suggests that semi-volatile pesticides rapidly 
translocate from application surfaces to adjacent surfaces. We do not yet have 
information on the speed or extent of translocation for less volatile pesticides like 
pyrethroids. 

• Two types of locations were sampled in JAX, the application area and a play area. In 
general, the surface residue loadings were higher at the application area than at the play 
area. 

• The surface wipe samples collected in the CCC study were collected from two locations 
in each of the randomly selected rooms of the child care centers: a floor and desk 
top/table top surface. In general, the floor residue loadings were higher. 


61 



Detection Frequency: Total Surface Loading 



Chlorpyrifos Diazinon c-Perm t-Perm Cyfluthrin Cypermeth Esfenval 

ES23 NHEXAS-AZ IPA BSBH MNCPES LWW F=3CCC IP A OUDJAX-SCR IPA 

^^CHAMACOS IPA E^CPPAES IPA ESS CPPAES LWW CZZZCPPAESDC 
E=TESTHOUSE IPA HLD TESTHOUSE DC CKXS DIYC IPA C"~DDAYCARE IPA 


Figure 4.8 Detection frequencies for pesticides using total available residue collection methods. 














































Table 4.4 Median and 95 th percentile values for total available residues (ng/cm 2 ) by study. 


Esfenvalerate 

P95 

l 

1 

1 

1 


3.5 

1 

1 

l 

1 

I 

1 

1 

1 

1 

1 

1 

1 

1 

l 

l 

1 

1 

1 

1 

l 

51.0 

P50 

l 

i 

1 

1 


oo 

o 

o 

o 

V 

1 

1 

1 

I 

1 

I 

1 

1 

l 

1 

I 

I 

l 

l 

i 

l 

l 

l 

1 

1 

1 

3.200 

Cypermethrin 

P95 

l 

1 

1 

00 

o 

750.0 

1 

1 

l 

l 

l 

l 

1 

l 

1 

1 

l 

i 

l 

1 

I 

I 

1 

l 

1 

! 

I 

I 

P50 

l 

1 

! 

<0.006 

2.600 

1 

l 

1 

1 

I 

1 

l 

l 

1 

1 

I 

l 

1 

1 

1 

l 

l 

1 

1 

1 

i 

i 

I 

I 

Cyfluthrin 

P95 

1 

l 

i 

i 

oo 

o 

o 

4.30 

o 

o 

o 

o 

-'t 

o 

l 

l 

! 

I 

I 

l 

I 

1 

l 

l 

i 

I 

I 

1 

l 

i 

i 

! 

P50 

l 

l 

i 

i 

<0.006 

<0.006 

<0.006 

<0.050 

l 

l 

i 

i 

1 

1 

1 

l 

1 

1 

l 

l 

1 

l 

1 

l 

i 

i 

i 

i 

<D 

<u 

Oh 

P95 

l 

i 

i 

r—H 

o 

o 

67.0 

3.6 

I 

i 

i 

i 

l 

l 

i 

I 

l 

1 

i 

i 

I 

l 

I 

l 

! 

i 

i 

P50 

l 

l 

i 

i 

0.02 

2.90 

0.26 

0.20 

l 

i 

i 

i 

1 

l 

1 

I 

! 

! 

1 

l 


t 

i 

i 

i 

c-Permethrin 

P95 

1 

I 

i 

0.67 

32.00 

42.00 

1.70 

l 

i 

i 

i 

1 

l 

l 

i 

i 

i 

! 

l 

i 

j 

i 

i 

i 

i 

P50 

i 

1 

■ 

i 

0.009 

2.200 

0.210 

ooro 

i 

1 

i 

i 

i 

i 

l 


i 

i 

t 

1 

i 

1 

i 

i 

i 

i 

Diazinon 

P95 

o 

<N 

V 

3.5 

0.5 

3.3 

4.0 

TO 

I 

l 

i 

i 

! 

1 

i 

i 

i 

i 

1 

I 

21.0 

72.0 

! 

P50 

<2.000 

<3.500 

0.002 

oiro 

<0.002 

o 

Tf 

o 

o 

! 


i 

i 

l 

i 

i 

■ 


! 

OO 

rn 

5.5 

i 

i 

Chlorpyrifos 

P95 

7.5 

1.5 

0.9 

o 

o 

r6 

0.2 

1.3 

p 

© 

0.2 

9.6 

r-H 

as 

36.0 

62.0 

! 

1 

l 

i 

i 

P50 

<0.07 

o 

CN 

m 

© 

o 

0.53 

o 

o 

CO 

o 

© 

0.17 

0.61 

0.03 

1.40 

4.70 

o 

p 

ore 

i 

i 

J 

i 

i 


Method 

IPA Wipe 

LWW 

IPA Wipe 

IPA Wipe 

IPA Wipe 

IPA Wipe 

LWW 

LWW 

IPA Wipe 

Dep Coup 

IPA Wipe 

IPA Wipe 

Dep Coup 

IPA Wipe 

IPA Wipe 

IPA Wipe 

Study 

NHEXAS-AZ 

MNCPES 

CCC 

JAX-SCR 

JAX-AGG 

CHAMACOS 

CPPAES Pre 

CPPAES 

CPPAES 

CPPAES 

TESTHOUSE Pre 

TESTHOUSE 

TESTHOUSE 

DIYC Pre 

DIYC 

DAYCARE 




T3 

CD 

p 

C/5 

CCj 

0D 

s 


o 

c 


D 


o 

C/3 


<D 

a, 


i 

i 


63 












































CHLORPYRIFOS 

TOTAL SURFACE LOADING (ng/cm2) 



+ + + NHEXAS-A2 SILL WIPE • • • CCC FLOOR WIPE 

O O O CCC PLAY AREA WIPE * * # JAX-SCR WIPE 

AAA CHAMACOS WIPE 


DIAZINON 

TOTAL SURFACE LOADING (ng/cm2) 



+ + + NHEXAS-AZ SILL WIPE XXX MNCPES LWW 

• • • CCC FLOOR WIPE O O O CCC PLAY AREA WIPE 

* * * JAX-SCR WIPE A * * CHAMACOS WIPE 


CIS—PERM ETTHRIN 

TOTAL SURFACE LOADING (ng/cm2) 


TRANS-PERMETHRIN 
TOTAL SURFACE LOADING (ng/cm2) 




• • • CCC FLOOR WIPE 

* * * JAX-SCR WIPE 


O O O CCC PLAY AREA WIPE 
AAA CHAMACOS WIPE 


• • • CCC FLOOR WIPE 

* * * JAX-SCR WPE 


O O O CCC PLAY AREA WIPE 
AAA CHAMACOS WIPE 


CYFLUTHRIN 

TOTAL SURFACE LOADING (ng/cm2) 


CYPERMETHRIN 

TOTAL SURFACE LOADING (ng/cm2) 




• •• CCC FLOOR WIPE O O O CCC PLAY AREA WIPE ••• CCC FLOOR WIPE O O O CCC PLAY AREA WIPF 

* * * JAX-SCR WIPE * * * JAX-SCR WIPE WIPE 


Figure 4.9 Lognormal probability plots for the most frequently detected pesticides which include 
chlorpyrifos, diazinon, cis- and /raHs-permethrin, cyfluthrin, and cypermethrin. 


64 








































LOADING (ng/cm2) LOADING (ng/cm2) LOADING (ng/cm2) 


CHLORPYRIFOS 

TOTAL SURFACE LOADING (ng/cm2) 


DIAZINON 

TOTAL SURFACE LOADING (ng/cm2) 



10000t 
1000 ! 
100 1 
10 -. 
11 
0.1 1 
0.01 
0.001 n 
0.0001 - 



AZ CCC JAX-SC JAX-AG CHA CPAE5 CPAES TEST TEST 

IPA IPA 1PA IPA LWW DC OC IPA 


AZ CCC JAX-SC JAX-AG OU DfYC 

IPA IPA IPA FA PA IPA 


CIS-PERMETHRIN 

TOTAL SURFACE LOADING (ng/cm2) 


TRANS-PERMETHRIN 
TOTAL SURFACE LOADING (ng/cm2) 


10000-1 
1000 - 
lOO-i 

10 -i 
11 
o.i - 
0.01 - 
0.001 - 


0.0001 - 




n-1-1-r 

CCC JAX-SC JAX-AC CHA 

IPA IPA IPA PA 


100001 
1000-j 
100 T 
10 


0.1 -i 
0.01 1 
0.001 1 
0.0001 : 



R 


n-1-1-r 

CCC JAX-SC JAX-AG CHA 

IPA IPA PA IPA 


CYPERMETHRIN 

TOTAL SURFACE LOADING (ng/cm2) 


ESFENVALERATE 

TOTAL SURFACE LOADING (ng/cm2) 




Figure 4.10 Box-and-whisker plots of total available residue surface loadings (ng/cm 2 ) for 
chlorpyrifos, diazinon, cw-permethrin, /rarcs-permethrin, cypermethrin, and esfenvalerate. 


65 



























































































4.4 Transferable Residue Measurements 


Transferable residue methods are intended to represent the surface loading that may be 
transferred as a result of contact with the contaminated surface; that is, instead of complete 
removal, they are typically intended to mimic transfer to skin during a single dermal contact with 
a surface, where transfer is aided by only saliva, sweat, or the sebum layer on the skin. 
Transferable residue loadings were measured in: 

• MNCPES using the Cl 8 press sampler on floors and non-floor surfaces, 

• CTEPP using surface wipes with 2 mL 75% IP A on hard-surface floors and counters and 
a PUF roller on carpeted floors, 

• CCC using the Cl8 press sampler on carpeted floors, 

• JAX using the Cl8 press sampler on carpeted floors, 

• CHAMACOS using the Cl8 press sampler on carpeted floors, 

• Test House using the Cl8 press sampler and a PUF roller skin on carpeted floors, 

• DIYC using the PUF roller on both hard-surface and carpeted floors, and 

• Daycare using the Cl8 press sampler and the PUF roller on carpeted floors. 

The Modified Cl 8 Surface Press Sampler was based on the original EL Sampler designed by 
Edwards and Lioy to collect pesticides in house dust from carpeted floors (Edwards and Lioy, 
1999; Hore, 2003). EPA modified the press sampler to use two 9-cm diameter sampling discs 
for a total sampling area of 114 cm 2 and eliminated the spring mechanism, henceforth it became 
known as the Modified Cl8 Surface Press Sampler. Unlike vacuum methods that collect 
household dust from all depths of the carpet pile and base, the surface press sampler is designed 
to only contact and remove residue from the surface. The developers maintain that the sampler 
replicates the collection efficiency of human skin and reflects transfer from single hand press 
(Edwards and Lioy, 1999; Lioy et al, 2000), ignoring the inter- and intra-individual factors that 
may affect transfer. 

The PUF roller transferable residue sampler was developed to simulate the pressure applied to a 
surface by a crawling child weighing 9 kg (7,300 Pa) (Hsu et al., 1990). The PUF roller consists 
of a weighted roller fitted with a thick, moistened polyurethane foam (PUF) cover. 

Modifications include using either a dry PUF roller cover or a thinner PUF skin. More details 
can be found in the literature (Hsu et al, 1990; Lewis et al. , 1994; Stout and Mason, 2003). 

Discussion of the CTEPP surface wipe samples is included here rather than in Section 4.3 
because of the small volume (only 2 mL) of isopropyl alcohol used. Also, it should be restated 
that in CTEPP transferable residue samples were only collected in those homes and daycare 
centers that reported recent pesticide use. 

Limits of detection for each method and chemical are given by study above in Table 4.2. 
Detection frequencies are given in Figure 4.11. The Cl 8 Press and PUF roller results from 
Daycare are not included (or further discussed) due to extremely poor detection frequencies, with 
only one Cl 8 and two PUF samples above the limit of detection. 


66 



Pesticide Presence in Transferable Residues 


• Overall, the detection frequencies for transferable residues were substantially lower than 
those for total available residues. 

• Chlorpyrifos was detected in greater than 75% of transferable residues in all of the 
studies except MNCPES. 

• Cis- and ^ra^-permethrin were detected in greater than 50% of the transferable residue 
samples collected in CTEPP. These measurements were made in a subset of homes with 
recent indoor applications of unidentified pesticides. 

• Transferable residues were rarely detected in field studies by the modified Cl 8 surface 
press sampler. In CHAMACOS, the detection frequency for chlorpyrifos was zero. In 
MNCPES, the detection frequencies on the floor and on other surfaces were 8 and 5 
percent, respectively. The only exception was the DIYC study, where the post¬ 
application detection frequency for diazinon was greater than 50%. 

• The modified C18 press sampler was more successfully used in the laboratory studies 
(Test House and Food Transfer studies) where residues were measured on all surface 
types sampled. 

• CTEPP used EPA wipes with only 2 mL isopropanol instead of the 10 to 20 mL often 
applied for total available residue measurements. It is likely that the amount of pesticide 
residue recovered from the sampled surfaces is influenced by the amount of IP A applied 
to the wipe. Other variables that should be considered include location sampled within 
the room and last known pesticide application. 


67 




Detection Frequency: Transferable Residues 



ffffiF) MNCPES PRESS CTEPP-NC IPA F=I CTEPP-NC PUF 

^CTCTEPP-OH IPA QUnCTEPP-OH PUF UZZZZk TESTHOUSE PUF 

E2Z3 TESTHOUSE PRESS PET PUF KSSDIYC PRESS 


Figure 4.11 Detection frequencies for pesticides using transferable residue collection methods. 
All results from the Cl 8 Press samplers used in CHAMACOS were below the limits of 
detection. 


68 

































































Transferable Residues: Summary Findings 

Transferable residue loadings at the median and 95 th percentile are given in Table 4.5 for all of 
the pesticides that were detected across studies (complete summary statistics are listed in Tables 
A.25 through A.29 in Appendix A). Transferable residue loadings of chlorpyrifos, diazinon, and 
permethrin are depicted in lognormal probability plots and box-and-whisker plots in Figures 4.12 
and 4.13, respectively. 

• The original Cl 8 press sampler was designed to represent what adheres to the skin from a 
single hand press onto a carpeted surface. The uses for the modified Cl 8 surface press 
sampler have expanded to include hard surfaces and longer contact times, contrary to its 
intended use. The data in Table 4.5 suggest that the sensitivity of the modified Cl 8 
surface press sampler is not adequate to measure typical residential pesticide residue 
levels due to its low collection efficiency (estimated as less than 1%). 

• The mean transferable (2 mL IPA wipe) loadings were significantly different between 
CTEPP NC and OH for c/s-permethrin (p<0.01), /ra/«-permethrin (p<0.05), and diazinon 
(p<0.01). The mean loadings were not significantly different for either chlorpyrifos 
(ANOVA, p=0.12) or cyfluthrin (ANOVA, p=0.17). 

• Wipe sampling methods varied in the volume of IPA used as a solvent (Table 4.1). The 
2-mL IPA wipes used in CTEPP produced surface loading values that were very similar 
to those produced with the PUF roller (Figure 4.13). Since the PUF roller is a 
transferable residue method, it appears that the amount of IPA applied to the wipe 
determines the type of surface residue collected (i.e., total or transferable residue). 
Interpretation of these results is complicated by other factors including recent application 
and sampling location with respect to application. 


69 



tVi 

Table 4.5 Median and 95 percentile values for transferable residues (ng/cm 2 ) by study. 


& 

P95 

1 

l 


r-~ 

o 

© 

o 

! 

1 

1 

1 

1 

1 

l 

* 

P50 

1 

l 


<0.001 

i 

i 

1 

1 

1 

1 

I 

P-I 

P95 

1 

1 

0.024 

0.033 

i 

1 

I 

! 

l 

1 

u 

H 

P50 

l 

l 

»/■> 

o 

o 

© 

0.001 

i 

i 

1 

l 

i 

i 

I 

I 

| 

P95 

! 

<0.007 

o 

o 

i 

i 

1 

1 

i 

i 

1 

l 

% 

O 

P50 

j 

o 

o 

o 

V 

c-~ 

o 

© 

o 

V 

i 

i 

1 

l 

i 

i 

! 

<D 

P95 

i 

i 

009T 

0.790 

i 

i 

I 

I 

i 

i 

i 

i 

<3 

Ph 

4, 

P50 

i 

i 

0.034 

0.005 

i 

i 

1 

l 

i 

i 

i 

d 

a> 

P95 

i 

i 

o 

o 

<Y-> 

o 

oo 

o 

o 

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i 

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i 

u 

P50 

i 

i 

o 

o 

© 

0.005 

! 

! 

i 

i 

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3 

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P95 

eri 

0.51 

0.05 

i 

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24.0 

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Q 

P50 

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<0.005 

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ro 


P95 

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1 

l 

1 

1 

& 

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2 

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P50 

<0.330 

r-~ 

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0.002 

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o 

o 

0.230 

l 

1 

1 

1 

Method 

Press 

IPA Wipe 

IPA Wipe 

PUF 

Press 

PUF 

Press 

Study 

MNCPES 

CTEPP-NC h 3 

CTEPP-OH h 3 

TESTHOUSE 

TESTHOUSE 

PET 

DIYC 


u 


T3 

<L> 

T3 

J3 

O 

X 

<D 

t/5 


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c n H 
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c >> 
4) "3 

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•4-* d> 

w a 
<l> a 
a, o 

I CO 


70 


























CHLORPYRIFOS 

TRANSFERABLE RESIDUE LOADING (ng/cmZ) 


DIAZINON 

TRANSFERABLE RESIDUE LOADING (ng/cm2) 



* * * 
tt a « 

n n n 
o o o 
© © © 
09 Z> C? 


CTEPP-NC HOME COUNTER WIPE 
CTEPP-NC HOME FLOOR PUF 
CTEPP-NC HOME FLOOR WIPE 
CTEPP-OH HOME COUNTER WIPE 
CIEPP-OH HOME FLOOR PUF 
CTEPP-OH HOME FLOOR WIPE 


* * * CTEPP-NC HOME COUNTER WIPE 
» « a CTEPP-NC HOME FLOOR PUF 

n n n ctepp-nc home floor wipe 

o o O CTEPP-OH HOME COUNTER WIPE 
© © © CTEPP-OH HOME FLOOR PUF 
<9 <9 CTEPP-OH HOME FLOOR WIPE 


CIS-PERMETHRIN 

TRANSFERABLE RESIDUE LOADING (ng/cm2) 


TRANS-PERMETHRIN 

TRANSFERABLE RESIDUE LOADING (ng/cm2) 



.1 .2 .5 1 2 5 10 2D 30 40506070 80 90 95 99 99.9 

Percent 


* * * CTEPP-NC HOME COUNTER WIPE 
a a « CTEPP-NC HOME FLOOR PUF 
P d n CTEPP-NC HOME FLOOR WIPE 
o o o CTEPP-OH HOME COUNTER WIPE 
© © © CTEPP-OH HOME FLOOR PUF 
<9 (9 (9 CTEPP-OH HOME FLOOR WIPE 



.1 .2 .5 1 2 5 10 20 30 405060 70 80 90 95 99 99.9 

Percent 


* * * CTEPP-NC HOME COUNTER WIPE 
a a a ctepp-nc home floor puf 
n n n ctepp-nc home floor wipe 
POP CTEPP-OH HOME COUNTER WIPE 
© © ffl CTEPP-OH HOME FLOOR PUF 
<9 <9 V CTEPP-OH HOME FLOOR WIPE 


Figure 4.12 Lognormal probability plots for transferable residue loadings for the most frequently 
detected pesticides which include chlorpyrifos, diazinon, and cis- and £raws-permethrin from 


CTEPP. 


71 



























CHLORPYRIFOS 

TRANSFERABLE RESIDUE LOADING (ng/cm2) 


DIAZINON 

TRANSFERABLE RESIDUE LOADING (ng/cm2) 



100- 



1 - 


o.i - 


o.oi - 


o.ooi - 



0.0001 - 


T 


NC HM NC HM OH HM OH HM TEST TEST 
IPA PUP IPA PUP PUP PRESS 


NC HM NC HM OH HM OH HM PET 

IPA POF IPA PUF PUF 


CIS-PERMETHRIN 

TRANSFERABLE RESIDUE LOADING (ng/cm2) 


TRANS-PERMETHRIN 

TRANSFERABLE RESIDUE LOADING (ng/cm2) 


CM 

E 

o 

\ 

CD 

c 


o 


□ 

< 

o 


100-1 
1°1 
11 
0.1 - 

0.01 •; 

0.001 - 



100 - 
. 10 ] 
1 - 

0.1 - 

0.01 - 


0.001 - 



0.0001 - 


0.0001 - 

-1-1-1-r 


NC HM NC HM OH HM OH HM 

IPA PUF IPA PUF 


NC HM NC HM OH HM OH HM 

IPA PUF IPA PUF 


CYFLUTHRIN 

TRANSFERABLE RESIDUE LOADING (ng/cm2) 


TCPY 

TRANSFERABLE RESIDUE LOADING (ng/cm2) 




Figure 4.13 Box-and-whisker plots for transferable residue loadings for the most frequently 
detected pesticides which include chlorpyrifos, diazinon, cis- and rrarcs-permethrin cyfluthrin 
and TCPy. 


72 






















































































4.5 Spatial and Temporal Variability 


Spatial and temporal variability were investigated in studies involving recent pesticide 
. applications, including: 

• Test House using IP A wipes, deposition coupons, Cl 8 press sampler and PUF roller; 

• CPPAES using IPA wipes, deposition coupons, and the LWW sampler; 

• DIYC using IPA wipes and Cl8 press; and 

• Daycare study using the IPA wipes. 

In studies with a series of measurements over time, the interval of time between measurements 
ranged from one to three days. In CPPAES, multiple rooms in ten homes were monitored for 
two weeks post application. In DIYC, multiple surfaces in three homes were monitored for one 
week. In the Test House, multiple surfaces in multiple rooms of a single house were monitored 
for 21 days. The Daycare study included multiple applications, each separated by one to three 
months, in a single daycare facility. In addition to sampling main activity areas, some studies 
also sampled less frequently contacted areas. 

Figure 4.14 presents total available surface residue loadings measured in multiple locations in 
multiple rooms over time in the Test House, in multiple rooms in ten homes in CPPAES, and on 
multiple surfaces in three homes in DIYC. Figure 4.15 presents transferable residue 
measurements over time in multiple rooms of the Test House and on multiple surfaces in three 
homes in DIYC. Figure 4.16 presents total available residue measurements from the Daycare 
study, collected immediately following applications on multiple surfaces in two rooms. Figure 
4.17 presents spatial variability in deposition coupon loadings in the kitchen (application site) 
and den (adjoining room) of the Test House following pesticide application. 

Spatial and Temporal Variability: Summary Findings 

• Preliminary examination indicates that total available residue loadings decay at a slower 
rate than airborne concentrations (See Figures 4.14 and 3.8). 

• In the Test House experiment, the transferable residue loadings appeared to decrease at a 
faster rate than the total available residues (Figures 4.14 and 4.15). This may have 
occurred because the pesticide residue became less available for transfer (for example, 
due to an interaction with the surface or because the dried residue was less available for 
transfer). 

• The transferable residues on the counters in DIYC (Figure 4.15) are nearly as high as 
those on the floors immediately after application, suggesting translocation of the pesticide 
from the site of application (assuming counters were not application surfaces). 

• Substantial variability within rooms (at times a 100-fold difference in loadings) is evident 
in the Daycare data (Figure 4.16). Exposure estimates using measurements at a single 
location based on an assumption of homogenous surface loadings may result in exposure 
misclassification. The spatial variability points to the need for sampling of multiple 
locations and perhaps for better resolution in the activity data that is gathered. 


73 


• Data from the Test House (Figure 4.17) show that surface loadings cannot be assumed to 
be homogenous within a room. 

• In the CCC study, loadings on floors were generally higher than loadings on table tops. 

• In a published analysis of the MNCPES LWW wipe data, Lioy and colleagues (2000) 
reported substantial variability in surface chlorpyrifos levels among different rooms. 


74 


EPA Test House-Chlorpyrifos CPPAES-Chlorpyrifos 




DIYC -Diazinon 



Figure 4.14 Total available surface residue loadings measured in multiple rooms over time in the 
Test House, in multiple rooms in ten homes in CPPAES, and on multiple surfaces in three homes 
in DIYC. 


EPA Test House - Chlorpyrifos 



DIYC • Diazinon 



Figure 4.15 Transferable residue measurements over time following an application from multiple 
locations in multiple rooms of the Test House and multiple surfaces in three homes in DIYC. 


75 















































Figure 4.16 Total available residue measurements from the Daycare study, collected immediately 
following applications on multiple surfaces in two rooms in a single daycare facility. Solid Line 
represents the preschool room and dashed line represents infant room 
Dotted vertical line represents application. 


Kitchen Deposition Coupon Loading Den Deposjtjon Coupon Loadjng 




Figure 4.17 Spatial variability in deposition coupon loadings in the kitchen (application site) and 
den (adjoining room) of Test House following pesticide application. 



























































































4.6 Differences Related to Location 


Regional Differences 

Studies dating back to the Non-Occupational Pesticide Exposure Study (NOPES) from 1986 to 
1988 (Whitmore et al, 1994) have reported regional differences in environmental pesticide 
concentrations and loadings. Differences are thought to result from heavier use of insecticides in 
warm weather climates with higher year round insect control problems than in colder regions 
where hard winters help to curb insect populations. 

• Median diazinon surface dust loadings (ng/cm 2 ) in home environments (daycares 
excluded) were very similar (about 0.002 ng/cm 2 ) across three states (NC, OH, and AZ, 
Table 4.3), and the 95 th percentiles were also somewhat similar (0.12, 0.31, and 0.18, 
respectively). ANOVA analysis with Bonferroni adjustment for multiple comparisons 
found no significant differences among the three locations. These dust measurements do 
not provide evidence of the geographic variations consistent with geographic differences 
in pest treatment practices reported by Colt (1998). 

• The overlapping distributions of pesticide concentrations in dust (ng/g) in the large 
observational field studies in Arizona, North Carolina, and Ohio (Figure 4.4) suggest that 
concentrations in dust may not be useful for determining region-specific pesticide use. 

• For transferable residues obtained with 2-mL IPA surface wipes, the mean chlorpyrifos 
and cyfluthrin loadings were higher for CTEPP-NC compared to CTEPP-OH but not 
statistically different (Figures 4.12, 4.13). However, the mean loadings were 
significantly higher in NC for c/s-permethrin (ANOVA; p<0.01) and ^ratts-permethrin 
(ANOVA; p<0.05) and marginally significant for diazinon (ANOVA; p<0.10). 

• Analysis of surface wipe samples from the national, probability-based Child Care Center 
study indicated no differences in the mean pesticide loadings among daycares in the four 
Census regions (data not shown, Tulve et al ., 2006). 

• Differences in surface sampling methods, year of the study, and time of year when 
samples were collected make it difficult to examine any regional differences in surface 
pesticide loadings in homes. The transferable residue measurements suggest higher 
levels in NC than in OH, but no systematic differences are evident in dust concentrations 
or total surface residue loadings, although JAX had much higher surface loadings than 
any of the other studies without recent applications. 

Urban vs. Rural 

Lu and colleagues (2004) recently reported that at least one organophosphate pesticide was 
present in the house dust of 75% of agricultural area homes but only 7% of metropolitan area 
homes, suggesting different exposure pathways for children living in agricultural and 
nonagricultural regions. While concerns about pesticides may be more obvious in farming and 
other rural areas, widespread elevated pesticide residue levels have also been reported in highly 
urbanized minority communities of New York City (Wliyatt et al., 2002). 


77 


• Neither the median nor 95 th percentile concentrations of chlorpyrifos measured in 
CHAMACOS dust was substantially higher than the median and 95 th percentile in the 
other studies (Table 4.3). The assumption that children living in agricultural areas 
experience higher exposures than children in nonagricultural regions is not supported by 
these chlorpyrifos in dust measurements. 

• Relatively high pre-application surface loadings in some of the CPPAES homes (data not 
presented) suggest possible contamination from pesticides applied in neighboring 
apartments in close proximity (Hore, 2003). Alternatively, the high loadings may suggest 
frequent treatments in those homes. 


4.7 Influential Factors 

As discussed above, the following factors appear to influence measured surface concentration or 

loading values: 

Collection Methods 

• The different types of collection methods are intended to have different collection 
efficiencies to serve different purposes. Efficiencies for various methods have been 
previously published. 

• Total residue methods (which use both solvent and mechanical action to remove residues 
that may have penetrated into the surface) produce the highest values, followed by dust 
methods, and then by transferable residue methods. 

• The low pesticide surface loadings obtained with 2 mL IPA wipes in both the NC and OH 
CTEPP studies (comparable to loadings obtained with the PUF roller) suggest that the 
amount of IPA applied to the wipe affects the amount of pesticide residue recovered. 

• The Cl 8 Press does not appear to be useful for determining typical surface pesticide 
residue loadings, for which it was never intended, because of its low collection efficiency 
and small size. 

Surface Types 

• Surface type has been shown to affect the collection efficiency of wipes. Recently 
published NERL data (Rohrer et al., 2003) found that wiping from hard surfaces greatly 
exceeded carpet, and tile generally exceeded hardwood. As stated by Rohrer, “Highest 
pesticide recoveries were from tile with diazinon (59%), chlorpyrifos (80%), and 
permethrins (52% cis; 53% trans ) being the only pesticides recovered by wiping at 
greater than 50% of the applied concentrations.” 

Sampling Locations 

• Despite evidence of translocation from direct application areas, the application area 
surface residue loadings were generally higher than the play area surface residue loadings 
in JAX. 


78 


• In the CCC study, floor residue loadings were typically higher than table top or desk top 
loadings. 

• Experiments in the Test House showed high spatial variability in loadings in the room of 
application (kitchen) and transport of pesticide residues to the adjoining room. 

• Results from the Daycare study showed substantial differences in surface loadings (up to 
two orders of magnitude) at different locations in a daycare center. 

Occupant Activities 

• Surface chlorpyrifos loadings were reportedly lower in the CPPAES homes in which the 
occupants performed cleaning activities and/or the homes that had high ventilation rates 
(Hore, 2003). 

• Crack and crevice applications in the unoccupied Test House produced higher surface 
loadings and longer decay times than the same type of application (albeit with less active 
ingredient released) in the occupied CPPAES homes. 

Pesticide Use Patterns 

• On a regional level, surface loadings in Jacksonville, Florida, an area likely to have year- 
round pest control issues and high pesticide usage, were much higher than in any of the 
other observational studies. 

• Within a given region, however, pesticide use information collected with questionnaires 
or inventories may not correlate with measured surface values. Published results from 
the MNCPES indicate that the residential pesticide use questions and overall screening 
approach used in the MNCPES were ineffective for identifying households with higher 
levels of individual target pesticides (Sexton et al., 2003). 

4.8 Correlations among Soil, Wipes, and Dust 

• Analysis of CCC data (Tulve et al ., 2006) found little correlation between surface wipe 
loadings and soil concentrations for 16 common organophosphate and pyrethroid 
pesticides. 

• In the CTEPP study, significant Spearman correlations between dust and soil 
concentrations were observed with diazinon (r=0.26, p<0.01) and TCPy (r=0.21, p<0.05) 
in NC homes and chlorpyrifos (r=0.28, p<0.01) and TCPy (r=0.20, p<0.05) in OH homes 
(data not presented). 

• Identification of correlations is hindered by the low detection frequencies for many 
pesticides in soil. 


79 


4.9 Particle-Bound Pyrethroid Residues: Implications toward Exposure 

The recent shift in commonly applied residential pesticides from organophosphate to pyrethroid 
compounds carries with it important implications for human exposure. The chemical and 
physical properties of a pesticide govern its behavior with respect to movement and fate. In 
general, pyrethroids have properties that favor the particulate phase, resulting in transport 
mechanisms preferentially involving dust rather than vapor. A tendency towards the particulate 
phase also suggests a decreased relative importance of the inhalation route and an increased 
relative importance of the dermal and indirect ingestion routes. 

Pesticides applied in homes translocate from the point of application and deposit onto non-target 
surfaces. Because human contact with target surfaces ( e.g ., cracks and crevices) is typically 
obstructed or otherwise hindered, it is largely the movement of residues from the point of 
application into the air and onto non-target surfaces that results in exposure. The movement of 
residentially applied insecticides follows a complex and poorly understood process of 
transformation and phase distribution and is influenced by several factors, namely: delivery 
system, application surface type, solvent, formulation, physicochemical properties of the active 
insecticide, and human and companion animal activity. 

Overall, pyrethroids have similar physicochemical properties, and as a result, they display 
similar behavior in the residential environment (Laskowski, 2002; Oros and Werner, 2005). 
Pyrethroids generally have low vapor pressures and Henry’s Law constants, thus they resist 
volatilization and exist almost entirely in the particulate phase at room temperature. They have 
high octanol/water partition coefficients (Ko W ), which suggests they tend to partition into lipids, 
and very high water/organic carbon partition coefficients (Ko C ), which suggests that they also 
tend to partition into organic matter. With these characteristics, pyrethroids can be expected to 
bind readily to the particulate matter that comprises house dust. Particles resuspended by human 
activity then act as the primary vector for pyrethroid transport and for human exposure. 

Particle-phase contaminant transfer is strongly particle size dependent (Rodes et al ., 2001). 

Kissel et al. (1996) reported that dermal adherence of dry soil primarily involves particles in the 
<150 pm size fraction. Assuming that house dust behaves similarly with respect to transfer, the 
size fraction that preferentially adheres to skin not only comprises the bulk of house dust, but 
also contains the highest pesticide concentrations. Rodes et al. (2001) reported that the <150 pm 
size fraction comprises about 60% of house dust. Pesticide concentrations in house dust increase 
with decreasing particle size, and are highest in the <25 pm size fraction (Lewis et al., 1999). 
Because the surface-to-volume ratio similarly increases with decreasing particle size, pesticides 
appear to be primarily attached to the surfaces of the particles (rather than trapped within). 

Particle-bound movement and transfer of pyrethroids imply a decreased importance of the 
inhalation route and an increased importance of the indirect ingestion route. Exposure of young 
children, for whom indirect ingestion of residues from object- and hand-to-mouth activities is 
particularly important, may be most strongly affected. Particle-bound residues may also have a 
reduced potential for dermal absorption, as a consequence of being bound to the particle. 


80 


5.0 DIETARY EXPOSURE MEASUREMENTS 


5.1 Introduction and Data Availability 

Diet can be a significant pathway of exposure to humans. Infants and young children may be 
particularly vulnerable to exposure by dietary ingestion because they eat more than adults do 
relative to their body weights. Foods may contain residues of pesticides because of intentional 
agricultural applications or they may become contaminated during processing, distribution, 
storage, preparation, and even consumption. The ingestion of residues on foods resulting from 
contact with hands and surfaces during consumption as well as the ingestion of pesticide residues 
while mouthing contaminated hands and objects are considered “indirect ingestion” pathways 
and are the subject of the next chapter (Chapter 6.0). This chapter provides a comparative 
summary of measurements of pesticides in duplicate diet samples and of estimated dietary 
intakes. The sample collection methods for the studies that included duplicate diet 
measurements are summarized in Table 5.1. 

Among the large observational studies, duplicate diet samples were collected in NHEXAS-AZ, 
MNCPES, and CTEPP. In CTEPP, food and beverage samples were collected at both homes and 
daycares. Duplicate diet samples were also collected in three pilot-scale studies, CHAMACOS 
(20 participants), DIYC (three participants), and JAX (nine participants). 

• The most common measure of dietary exposure was by composited duplicate diet 
analyses (Table 5.1). This approach reduces study costs compared to analyzing 
individual foods, but it increases the complexity of the sample analysis and produces 
higher method detection limits. 

• Duplicate diet samples measure the pesticide residues in the children’s foods after 
processing and preparation by the caregiver. The samples, therefore, may include 
residues from contaminated food handling surfaces in addition to the residues contained 
in the food products. However, duplicate diets fail to capture the additional intake of 
pesticides resulting from the child’s activities before and during consumption, as 
discussed in Chapter 6. 

* 

• Duplicate plate samples were used for dietary measurements at the daycares in CTEPP. 
The distinction between a duplicate plate and a duplicate diet (with the latter accounting 
for uneaten foods) is typically more important for children than adults because significant 
quantities of food may be left uneaten. 


81 


Table 5.1 Dietary exposure sample collection methods for pesticides. 


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82 




















5.2 Pesticide Presence 


Table 5.2 presents the detection limits for the studies. The frequency of detection for the 
selected pesticides is presented in Figure 5.1. The median and 95 th percentile concentrations are 
presented in Table 5.3. Data are presented in lognormal probability plots (Figures 5.2 and 5.3) 
for the large observational field studies and box-and-whisker plots (Figures 5.4 and 5.5) for all of 
the studies. Where food mass measurements are available (Table 5.1), both concentration and 
intake (mass of compound ingested) are presented. Intake is defined as pg/day in keeping with 
the dietary exposure algorithm of the Draft Protocol (Berry et al. , 2001) rather than as pg/kg- 
bw/day which would be more consistent with the reference dose (RfD) paradigm. 

• Reported method detection limits for chlorpyrifos ranged from 0.04 pg/kg in JAX up to 
1.7 pg/kg in CHAMACOS (Table 5.2). 

• Chlorpyrifos was detected in over 50% of the duplicate diet samples in MNCPES, 

CTEPP, and JAX (Figure 5.1). The median chlorpyrifos concentrations in the MNCPES 
and JAX diet samples were at least twice as high as in the CTEPP samples (Table 5.3). 

• Diazinon was not frequently detected in any of the studies except DIYC, a study in which 
there had been prior indoor applications. The data from DIYC suggest that 
contamination of food due to handling and surface contact is important in homes with 
recent applications (see Section 6). 

• While detection of diazinon in food samples was typically below 30% (Figure 5.1), 
detection immediately following crack and crevice application in DIYC was 100%. 

• The logplots (Figures 5.2 and 5.3) show that in the upper half of the distribution (between 
the 50 th and the 95 th percentiles), higher concentrations of cis- and /raws-permethrin were 
measured in solid food in North Carolina homes than in North Carolina daycares or Ohio 
homes or daycares. 

• Model simulations using DIYC data (results not presented) revealed that pesticides 
transferred to food during contact with surfaces and handling by a child may increase 
dietary intake significantly (over 60% under the modeled scenario). 

• Published results from the MNCPES (Clayton et al, 2003) showed that extant residue 
databases can successfully be used to select samples for analysis, potentially reducing 
costs by avoiding analyses of foods not likely to contain measurable levels. Care must be 
taken, however, to avoid neglecting those residues that are transferred during handling. 

• Measurable levels of these particular pesticides were rarely detected in beverages in any 
of these studies. Future studies with other such pesticides that are not expected to be 
found in drinking water may consider eliminating this costly measurement. 

• Infants and children consume far fewer types of foods than do adults (while consuming 
much more of certain foods) (NRC, 1993). Thus, the number of days of collection may 
be less important for children than for adults. 

• The large potential for enzymatic degradation of pesticides (especially chlorpyrifos) 
during food sample storage and during homogenation prior to analysis has not been 
directly addressed by any studies under this program. 


83 


Table 5.2 Limits of detection (pg/kg) for pesticides measured in duplicate diets. 


Study 

Compounds 

Chlorpyrifos 

Diazinon 

m-Permethrin 

rraws-Permethrin 

Cyfluthrin 

NHEXAS-AZ 

1.0 

0.7 

a 

— 

— 

MNCPES 

0.26 

0.3 

0.2 

0.2 

— 

CTEPP 

0.08 

0.08 

0.08 

0.08 

0.83 

JAX 

0.04 

0.04 

0.02 

0.02 

0.4 

CHAMACOS 

1.4 

1.2 

4.5 

2.9 

— 

DIYC 

— 

0.36- 1.25 

— 

— 

— 


a Blank cells (—) indicate that the pesticide was not measured in the study. 


Table 5.3 Median and 95 th percentile pesticide concentrations (pg/kg) measured in duplicate diet 
food samples. 


Study 

Chlorpyrifos 

Diazinon 

cA-Permethrin 

//YZHS-Permethrin 

Cyfluthrin 

P50 

P95 

P50 

P95 

P50 

P95 

P50 

P95 

P50 

P95 

NHEXAS-AZ 

BDL a 

5.7 

1.8 

1.9 

_b 

— 

— 

-- 

— 

— 

MNCPES 

0.53 

2.4 

BDL 

0.38 

— 

— 

~ 

— 

-- 

— 

CTEPP-NC Home 

0.2 

2.1 

BDL 

0.4 

BDL 

15.6 

BDL 

8.7 

BDL 

0.9 

CTEPP-NC Daycare 

0.1 

0.9 

BDL 

0.2 

BDL 

5.2 

BDL 

3.0 

BDL 

BDL 

CTEPP-OH Home 

0.2 

1.6 

BDL 

0.2 

BDL 

8.8 

BDL 

8.0 

BDL 

BDL 

CTEPP-OH Daycare 

0.1 

0.6 

BDL 

0.2 

BDL 

2.2 

BDL 

1.4 

BDL 

BDL 

JAX 

0.38 

7.4 

BDL 

1.0 

0.29 

13 

0.22 

22 

BDL 

3.6 

CHAMACOS 

BDL 

1.4 

BDL 

BDL 

BDL 

BDL 

BDL 

BDL 

— 

— 

DIYC 

— 

~ 

0.17 

0.78 

— 

— 

— 

— 

— 

— 


a BDL, Below minimum detection limit 

b Blank cells (--) indicate the pesticide was not measured in the study 


84 







































Detection Frequency: Solid Food 


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90 - 
80 - 
70 - 
60 
50 - 
40 - 


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Q 

20 - 

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o-J 


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Chlorpyrifos Diazinon c-Perm t-Perm Cyfluthrin TCPy 

ES5SS NHEXAS-AZ MNCPES BSSH CTEPP-NC HOME TOmCTEPP-NC DAYCARE 

E53Z23 CTEPP-OH HOME ^^CTEPP-OH DAYCARE nun JAX GZnCHAMACOS KXEDIYC 


Figure 5.1 The detection frequency of pesticides measured in duplicate diet food samples. 


85 






























































































CHLORPYRIFOS 

SOLID FOOD CONCENTRATION (ug/kg) 


CHLORPYRIFOS 
SOLID FOOD INTAKE (ug/doy) 




+ + + NHEXAS-AZ 
* * * CTEPP-NC HOME 
«> O O CTEPP-OH HOME 


XXX MNCPES 
□ a □ CTEPP-NC DAYCARE 
AAA CTEPP-OH DAYCARE 


XXX MNCPES Y Y Y CTEPP-NC 

Z Z Z CTEPP-OH 


DIAZINON 

SOLID FOOD CONCENTRATION (ug/kg) 


DIAZINON 

SOLID FOOD INTAKE (ug/day) 



+ + + NHEXAS-AZ XXX MNCPES 

* * * CTEPP-NC HOME □ □ □ CTEPP-NC DAYCARE 

o o o CTEPP-OH HOME AAA CTEPP-OH DAYCARE 



XXX MNCPES Y Y Y CTEPP-NC 

Z Z Z CTEPP-OH 


CIS-PERMETHRIN 

SOLID FOOD CONCENTRATION (ug/kg) 


CIS-PERMETHRIN 
SOLID FOOD INTAKE (ug/day) 




XXX MNCPES * * * CTEPP-NC HOME 

□ □ □ CTEPP-NC DAYCARE O O © CTEPP-OH HOME XXX MNCPES Y Y Y CTEPP-NC 

AAA CTEPP-OH DAYCARE Z Z Z CTEPP-OH 


Figure 5.2 Lognormal probability plots of solid food concentrations (pg/kg) and intakes (pg/day) 
for chlorpyrifos, diazinon, and m-permethrin from large observational field studies. 


86 






















































TRANS-PERMETHRIN 
SOLID FOOD CONCENTRATION (ug/kg) 


TRANS-PERMETHRIN 
SOLID FOOD INTAKE (ug/doy) 



XXX MNCPES * * * CTEPP-NC HOME 

□ □ □ CTEPP-NC DAYCARE O O O CTEPP-OH HOME 
AAA CTEPP-OH DAYCARE 



XXX MNCPES Y Y Y CTEPP-NC 

Z Z Z CTEPP-OH 


TCPY 

SOLID FOOD CONCENTRATION (ug/kg) 


TCPY 

SOLID FOOD INTAKE (ug/day) 



* * * CTEPP-NC HOME □ □ □ CTEPP-NC DAYCARE 

o © o CTEPP-OH HOME AAA CTEPP-OH DAYCARE 



IMP 

SOLID FOOD CONCENTRATION (ug/kg) 


IMP 

SOLID FOOD INTAKE (ug/day) 




Figure 5.3 Lognormal probability plots of solid food concentrations (pg/kg) and intakes (pg/day) 
for /raws-permethrin, TCPy, and IMP from large observational field studies. 


87 















































CONCENTRATION (ug/kg) CONCENTRATION (ug/kg) CONCENTRATION (ug/kg) 


CHLORPYRIFOS 

SOLID FOOD CONCENTRATION (ug/kg) 


CHLORPYRIFOS 
SOLID FOOD INTAKE (ug/day) 




DIAZINON 

SOLID FOOD CONCENTRATION (ug/kg) 


DIAZINON 

SOLID FOOD INTAKE (ug/day) 




CIS-PERMETHRIN 

SOLID FOOD CONCENTRATION (ug/kg) 


CIS-PERMETHRIN 
SOLID FOOD INTAKE (ug/day) 


1000 ; 

100 - 

10; 

11 
0.1 ; 

0.01 1 
0.001 - 
0.0001 - 

r 

MN 



“i- 1 - 1 - 1 -r 

NC HM NC DC OHtW OHOC JAX 



Figure 5.4 Box-and-whisker plots of solid food concentrations (pg/kg) and intakes (pg/day) for 
chlorpyrifos, diazinon, and c/s-permethrin across all studies. 


88 






































































CONCENTRATION (ug/kg) CONCENTRATION (ug/kg) CONCENTRATION (ug/kg) 


TRANS-PERMETHRIN 
SOLID FOOD CONCENTRATION (ug/kg) 


TRANS-PERMETHRIN 
SOLID FOOD INTAKE (ug/day) 


1000 1 
100 1 
10 = 

1 

0.1 1 _L 
0.01 1 
0.001 1 
0.0001 - 

-r 

UN 



i- 1 - r~ 

NC HU NC DC OH HJ 



~i-r 

OH DC JAX 



TCPY 

SOLID FOOD CONCENTRATION (ug/kg) 


TCPY 

SOLID FOOD INTAKE (ug/day) 




IMP 

SOLID FOOD CONCENTRATION (ug/kg) 


IMP 

SOLID FOOD INTAKE (ug/day) 




Figure 5.5 Box-and-whisker plots of solid food concentrations (pg/kg) and intakes (pg/day) for 
Jraws-permethrin, TCPy, and IMP across all studies. 


89 


















































5.3 Relative Importance of the Ingestion Route 

The Stochastic Human Exposure and Dose Simulation (SHEDS) model (Zartarian et al., 2000) 
prediction for dietary intake of c/s-permethrin is compared to CTEPP measurements in Figure 
5.6. The estimated proportion of aggregate exposure represented by dietary intake for CTEPP- 
NC and CTEPP-OH children is from the CTEPP Report (Morgan et al., 2004) and is presented in 
Figures 5.6 and 5.7, respectively. 

• An example of use of the SHEDS model to predict dietary intake of cw-permethrin in a 
study population is shown in Figure 5.6. The dietary intake estimates may then be 
compared to SHEDS model estimates of intake by other relevant routes to determine the 
relative importance of the ingestion route. 

• Based on route-specific estimates (Figures 5.7 and 5.8), dietary ingestion represents the 
dominant route of exposure for chlorpyrifos, diazinon, and permethrin in the CTEPP 
study. Indirect ingestion, estimated based on dust and soil measurements, is a far greater 
concern for the permethrin than for chlorpyrifos and diazinon in the CTEPP study. 

• The route that represents the dominant route of exposure (dietary ingestion) is also the 
route with the lowest detection frequencies (approximately 2/3 of the values for 
permethrin in CTEPP are nondetects), which increases the uncertainty in the estimates. 
Substituting a fraction of the detection limit for values below the limit of detection may 
have a disproportionate impact on the outcome. 



t i . T i i i r— - i - 

45 50 55 60 65 70 75 80 85 90 95 


Percentile 

| SHEDS model —° — Observed data | 

Figure 5.6 Comparison of SHEDS model prediction for dietary intake of c/s-permethrin 
(pg/kg/day) and CTEPP measurement data. 


90 






















Cliloipyrifos 

r2% 


r j\ 

L J 


TCP 





cis -P 




trans -P 


2,4-D 


Inhalation 


Dietary 


Indirect 


Figure 5.7 Estimated mean proportion of aggregate potential exposure for CTEPP-NC children 
by exposure route. (TCP = 3,5,6-Trichloro-2-pyridinol; cis -P and trans-? - cis- and trans- 
Permethrin; 2,4-D = 2,4-Dichlorophenoxyacetic acid.) From Morgan et al., 2004. 


91 


























5% 


4% 


Chloipyiifos 


TCP 

4 % 





trans -P 



Diazinon 

4% 


cis- P 




2,4-D 



Inhalation 


Dietary 


Indirect 


Figure 5.8 Estimated mean proportion of aggregated potential exposure for CTEPP-OH children 
by exposure route. (TCP = 3,5,6-Trichloro-2-pyridinol; cis -P and trans -P = cis- and trans- 
Permethrin; 2,4-D = 2,4-Dichlorophenoxyacetic acid.) From Morgan et al., 2004. 


92 































6.0 INDIRECT INGESTION MEASUREMENTS 


Children’s ingestion of pesticide residues is not limited to residues in food and beverages 
acquired during cultivation, food production, and in-home preparation. Indirect ingestion refers 
to the ingestion of residues from hands or objects that enter the mouth, as well as to the ingestion 
of residues transferred to food items by contact with the floor or other contaminated surfaces 
during consumption. Indirect ingestion is believed to be an important route of exposure for 
children because of their frequent mouthing activities and their unique handling of foods while 
eating. Indirect ingestion may be the result of hand-to-mouth, object-to-mouth, or hand-to- 
object-to-mouth activity. Indirect ingestion may be estimated using an approach that lumps 
some of the exposure factors and activity patterns associated with indirect ingestion. This 
simplified approach allows for assessment of indirect ingestion exposure based on measurement 
data collected in the field and on factors that characterize the activities that lead to indirect 
ingestion. In this approach, objects (including food) that are commonly handled, mouthed, 
and/or ingested are identified in the field. The residue loadings on these objects are measured 
directly or estimated from surface loading measurements combined with transfer efficiencies 
measured in the laboratory. General information relating to the frequency and nature of these 
mouthing and ingestion activities is also collected. Data on the fraction of residues that may be 
removed from an object during mouthing that has been collected in the laboratory is then 
required to complete the assessment. In addition, the items identified as most often mouthed 
and/or eaten are assumed to represent the most significant sources of indirect ingestion exposure. 
This section presents summary data for studies addressing the indirect ingestion route of 
exposure (Table 6.1). Highlights of the data are presented below. 

6.1 Characterizing Hand- and Object-to-Mouth Activities 

Exposure models are based on two factors: how much pesticide residue is available for human 
uptake and what human activities occur that would result in contact with and uptake of residues. 
Hand-to-mouth and object-to-mouth activities are believed to directly impact ingestion of 
pesticides among children through the indirect ingestion exposure route, but the relative 
importance of these activities has not been established. In fact, the lack of empirical data 
showing that either hand- or object-to-mouth activities appreciably affect exposure makes it a 
hypothesis that has not yet been adequately addressed. The frequency of hand-to-mouth, object- 
to-mouth, and/or combo-to-mouth contacts were quantified for children in the MNCPES and 
CPPAES studies using a computer software system (Table 6.2). These studies used Virtual 
Timing Device (VTD) software (Zartarian et al.. 1997) to quantify the children’s normal daily 
activities captured on videotape. The following are highlights of the data from these studies. 

• Assigning contact as either a hand-to-mouth or an object-to-mouth contact can cause the 
hand-to-mouth and/or object-to-mouth contacts per hour to be underestimated. A combo- 
to-mouth category that accounts for both simultaneous types of contacts may provide a 
more accurate estimate of the indirect ingestion route of exposure. 

• An average frequency of 9 hand-to-mouth contacts per hour among 2 to 5 year olds is 
recommended for regulatory risk assessments (US EPA, 2002). The CPPAES results 
suggest that a higher value may be appropriate (Table 6.3). 


93 




• Figure 6.1 presents the average frequency of hand- and object-to-mouth contacts during 
all eating and non-eating events. The highest hand-to-mouth frequency was observed in 

CPPAES. 

• Factors affecting hand-to-mouth contact frequencies may include inclusion of eating 
events, amount of time on tape, types of activities, number of children, and age range. 

• An analysis of hand-to-mouth activities in MNCPES has been published by Freeman et 
al (2001). They reported that hand-to-mouth activities were significantly more frequent 
(t test, P<0.05) among girls than among boys. 

• The MNCPES data also showed that hand-to-mouth and object-to-mouth activities were 
more frequent (Mann-Whitney, p<0.05) indoors than outdoors (Freeman et al, 2001). 

• Published studies have quantified the hand- and object-to-mouth activities of young 
children (Zartarian et al., 1998; Reed et al, 1999; Tulve et al, 2002; Freeman et al, 
2005). These studies suggest that young children may exhibit higher hand-to-mouth 
and/or object-to-mouth contacts than older children and adults. 

• Standardized approaches for quantifying the activity patterns of children are needed in 
order to compare results among different studies. 


6.2 Residue Loadings on Mouthed Objects and Removal by Mouthing 

For indirect ingestion estimates, objects that are commonly mouthed are identified in the field 
and the residue loadings on these objects are measured. Objects commonly mouthed by 
preschoolers were identified in CTEPP. Pesticide loadings on toy surfaces were measured in the 
CHAMACOS and CPPAES studies. Data on the fraction of residues that may be removed by 
mouthing of fingers was collected in the laboratory-based Transfer studies using non-toxic 
fluorescent surrogates. 

• Objects commonly mouthed by preschoolers were identified in CTEPP. These items 
were typically toys and food-related items (Table 6.4). 

• Chlorpyrifos loadings on toy surfaces were much higher following recent applications, as 
evidenced by the higher values in CPPAES than in CHAMACOS (Table 6.5). Loading 
on toy surfaces in CPPAES (Table 6.5) were greater than surface loadings as measured 
by deposition coupons (Table 4.4). 

• Measurements from CPPAES (data not presented) suggest that surface wiping of plush 
toys yields only a small fraction of the total amount of chlorpyrifos absorbed into the toys 
(as measured by extraction). Indirect ingestion among children who regularly mouth soft 
toys may thus be underestimated by toy surface wipes. 

• In “transfer off’ experiments conducted with a fluorescent tracer (riboflavin) as part of 
the Transfer studies, removal from skin via the mouthing of 4 fingers was measured. 

Eight replicates were performed with each of three participants (data not presented), with 
0 to 26% of the tracer removed per replicate (loss was significantly different from zero in 
only one-half of the replicates). 


94 


Table 6.1 Collection methods for the transfer of pesticide surface residues to food or objects. 


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Table 6.2 Videotaped children’s hand- and object-to-mouth activity details. 


Study 

N 

Age 

(years) 

Sampling 

Location 

Time Period 

Method of Analysis 

Activity of 
Interest 

Availability 

MNCPES 

19 

3 to 12 

Homes 

(inside 

and/or 

outside) 

4 consecutive 
hours in normal 
daily activities 

Methods of Reed et 
al, 1999 

Hand-to-mouth 
Obj ect-to-mouth 

Freeman et al., 
2001. 

CPPAES 

10 

2 to 5 

Homes 
(inside or 
outside) 

4 hours on Day 

2 following 
crack and 
crevice 
application of 
chlorpyrifos 

Computer software 
(Virtual Timing 
Device) 

Quantified 4 hours 
of videotape for 
both hands 

Hand-to-mouth 

Object-to-mouth 

Freeman et al., 
2004. 


Table 6.3 Videotaped hand-to-mouth and object-to-mouth counts. 


Study 

Hand-to-Mouth 

Object-to-Mouth 

Eating Events 

Mean 

Median 

Mean 

Median 

CPPAES (2 to 5 yrs) 

19.8 

16 

8.4 

6.4 

Unspecified 

Tulve a <24 month old 

18 

12 

45 

39 

Excluded 

Tulve >24 month old 

16 

9 

17 

9 

Excluded 

MNCPES (3 to 12 yrs) 

5.7 

2.5 

1.8 

0 

Unspecified 

MNCPES boys indoor 

4.7 

NR 

1.0 

NR 

Unspecified 

MNCPES girls indoor 

8.1 

NR 

2.6 

NR 

Unspecified 


NR, Not Reported 

a Tulve data (Tulve et al., 2002) included for comparison. 


Table 6.4 Objects commonly mouthed by preschoolers in CTEPP. 


Category 

Items 

Toys 

Plastic rings/bracelets, stuffed animals, balls, walkie talkie, building blocks, 
doll, bubble blower 

Food-Related Items 

Ice pops, candy wrapper, water bottle, utensils, napkins, drinks 

Miscellaneous 

Plastic blow-up chair, pens, greeting cards, clothing, CDs, towels, blanket, pets 


96 
































tVi 

Table 6.5 Median and 95 percentile pesticide loadings (ng/cm 2 ) measured on toy surfaces. 


Study 

Chlorpynfos 

Diazinon 

Cis-Permethrin 

frans-Permethrin 

cyfluthrin 

P50 

P95 

P50 

P95 

P50 

P95 

P50 

P95 

P50 

P95 

CHAMACOS 

BDL a 

0.15 

0.034 

0.27 

BDL 

0.053 

BDL 

0.072 

BDL 

BDL 

CPPAES 

3.0 

21 

_b 

— 

— 

— 

— 

— 

— 

— 


a BDL, Below minimum detection limit 

b Blank cells (—) indicate the pesticide was not measured in the study 



Figure 6.1 Comparison of the median hand-to-mouth and object-to-mouth contacts per hour 
among CPPAES and MNCPES children. MNCPES values are means instead of medians. Tulve 
data (Tulve et al ., 2002) included for comparison. 


97 



















































































































6.3 Transfer of Pesticide Residues to Food 


• The experiments reported here (Appendix B, Food Transfer Studies) used loadings that 
were near to or greater than the 95 { percentile for loadings in most of the recent field 
studies (See Table 4.4). 

• Higher pesticide transfer to food occurred from hard, smooth surfaces, such as hardwood 
flooring; lower transfer occurred from carpet. For example, 33% of chlorpyrifos was 
transferred from wood flooring to an apple, whereas the amount transferred from carpet 
was not enough to be reliably quantified (Table 6.6). 

• Bologna, a moist and fatty food, removed a higher percentage of pesticides from a hard 
surface than did fruit leather, a low-fat and low-water content food (Table 6.7). 

• Comparison (Table 6.8, Figure 6.2) of measured dietary intake of diazinon (incorporating 
excess contamination due to handling) with estimates predicted by the Children’s Dietary 
Intake Model (CDIM) suggests that use of fixed values for transfer efficiencies and for 
activity factors in the model may result in inaccurate estimates of daily dietary intake. 
Model-predicted estimates generally under-predicted intake. 

• Diazinon concentrations in untouched leftover food were compared with those in handled 
leftover food in DIYC. Daily dietary intake estimates accounting for contamination due 
to handling by children were often double the intake estimates based on untouched food 
(Total Measured Dietary Intake vs. Duplicate Diet Intake, Table 6.8), indicating that 
duplicate diets may significantly underestimate actual intake in homes that have high 
surface pesticide residue loadings. 

• Food transfer studies have provided evidence that transfer of pesticide residues from 
surfaces to foods is dependent on such factors as pesticide class, food type, contact 
duration, and contact force (data not presented). 

• Applied force produced a considerable increase in transfer efficiency (data not 
presented). Moreover, the effect of applied force was even more dramatic as contact 
duration increased. 


98 


Table 6.6 The transfer efficiency (percent transfer, mean ± sd) of pesticide residues from treated 
surfaces to foods (relative to transfer to IPA wipes), after a 10-min contact duration (Food 
Transfer Studies). 


Pesticide 

Sampling Media 

N 

Treated Surface 

Ceramic Tile 

Wood Flooring 

Carpet 

Chlorpyrifos 
(21-38 ng/cm 2 ) 

Bologna 

2 

36 ±20 

15 ± 4 

BQL a 

Apple 

2 

18 ± 5 

33 ±8 

BQL 

Cheese 

2 

7 ± 0 

26 ± 1 

BQL 

Diazinon 
(20-30 ng/cm 2 ) 

Bologna 

2 

41 ±5 

29 ±0 

BQL 

Apple 

2 

35 ±8 

50 ±5 

BQL 

Cheese 

2 

20 ±7 

103 ± 18 

BQL 

Malathion 
(33-45 ng/cm 2 ) 

Bologna 

2 

60 ±21 

31 ± 1 

BQL 

Apple 

2 

132 ±74 

18 ± 1 

212 ±60 

Cheese 

2 

94 ±33 

52 ±37 

400 ± 173 

m-Permethrin 
(40-53 ng/cm 2 ) 

Bologna 

2 

19 ± 15 

70 ±86 

BQL 

Apple 

2 

26 ± 13 

3 ± 1 

BQL 

Cheese 

2 

BQL 

BQL 

BQL 

/ra/is-Permethrin 
(43-55 ng/cm 2 ) 

Bologna 

2 

23 ±20 

10 ± 1 

BQL 

Apple 

2 

29 ± 14 

5 ± 0 

BQL 

Cheese 

2 

BQL 

BQL 

BQL 


a BQL = Below Quantitation Limit 


99 
























Table 6.7 The transfer efficiency (percent transfer, mean ± sd) of pesticide residues from a 
treated ceramic tile surface to various foods and to an IPA Wipe (Food Transfer Studies). 


Pesticide Class 

Pesticide 

Sampling Media 

N 

% Transfer 

Organophosphate 

Chlorpynfos 
(123 ng/cm 2 ) 

Bologna 

3 

64.7 ± 15.0 

Apple 

3 

27.5 ± 8.0 

Fruit Leather 

3 

13.5 ±2.0 

20-mL IPA Wipe 

3 

99.8 ± 10.8 

Malathion 
(193 ng/cm 2 ) 

Bologna 

3 

74.9 ± 17.7 

Apple 

3 

29.7 ± 8.4 

Fruit Leather 

3 

8.7 ±2.7 

20-mL IPA Wipe 

3 

104.6 ± 10.9 

Pyrethroid 

Cyfluthrin 
(143 ng/cm 2 ) 

Bologna 

3 

47.8 ± 13.4 

Apple 

3 

24.0 ± 3.4 

Fruit Leather 

3 

0.7 ±0 

20-mL IPA Wipe 

3 

108.5 ± 12.1 

Cypermethrin 
(185 ng/cm 2 ) 

Bologna 

3 

45.0 ± 10.7 

Apple 

3 

21.5 ±6.9 

Fruit Leather 

3 

0.6 ±0 

20-mL IPA Wipe 

3 

101.5 ±7.0 

Deltamethrin 
(211 ng/cm 2 ) 

Bologna 

3 

39.2 ±6.1 

Apple 

3 

22.2 ±5.1 

Fruit Leather 

3 

2.4 ± 0.2 

20-mL IPA Wipe 

3 

83.7 ±4.3 

Permethrin 
(147 ng/cm 2 ) 

Bologna 

3 

44.0 ± 11.5 

Apple 

3 

19.8 ±7.1 

Fruit Leather 

3 

1.3 ±0.1 

20-mL IPA Wipe 

3 

100.8 ±4.8 

Phenylpyrazole 

Fipronil 
(203 ng/cm 2 ) 

Bologna 

3 

43.3 ± 1.6 

Apple 

3 

30.9 ± 14.8 

Fruit Leather 

3 

2.0 ± 1.7 

20-mL IPA Wipe 

3 

103.8 ± 10.4 


100 






































Table 6.8 The measured and predicted ingestion (ng/day) of diazinon from the DIYC. 


Child 

Sampling 

Day 

Duplicate Diet 
Intake 

Excess Dietary 
Intake a 

Total Measured 
Dietary Intake b 

CDEM Predicted 
Dietary Intake c 

Percent 
Difference d 

ng/d 

ng/d 

ng/d 

ng/d 

% 

1 

Pre 

197 

384 

581 

357 

-39 

1 

1063 

1270 

2333 

1271 

-46 

4 

280 

220 

500 

281 

-44 

5 

270 

501 

771 

333 

-57 

6 

140 

322 

462 

142 

-69 

7 

563 

536 

1099 

702 

-36 

8 

253 

160 

413 

397 

-4 

2 

1 

455 

156 

611 

663 

9 

2 

233 

95 

328 

402 

23 

3 

212 

373 

585 

392 

-33 

4 

260 

414 

674 

612 

-9 

5 

188 

189 

377 

278 

-26 

3 

2 

95 

90 

185 

509 

175 

8 

412 

344 

756 

940 

24 


a Measured surface-to-food and hand-to-food transfer due to handling of foods, concentration in handled but uneaten 
portion extrapolated to eaten portion. 
b Duplicate Diet intake plus Excess Dietary intake. 

c Estimated by deterministic model using fixed transfer efficiency and activity values. 
d Percent Difference = 100*[(CDIM Predicted Intake - Total Measured Intake)/(Total Measured Intake)]. 


101 

























2500n 


— 2000 - 
3 ) 


£ 1500- 


J> 1000- 

o 

T3 
CD 


500- 


:/-■ - 


- 1 t | -1-1 

0 500 1000 1500 2000 2500 

Measured Intake (ng/d) 


Figure 6.2 Comparison of measured and predicted ingestion of diazinon (ng/day) from the 
DIYC. Dashed line represents a hypothetical slope of 1. Measured intake generally exceeds 
predicted intake, as indicated by the majority of points lying to the right of the dashed line. 


102 




6.4 Indirect Ingestion of Dust and Soil 

The potential indirect ingestion exposure (ng/day) can be estimated using indoor floor dust 
( n g/g) an d outdoor soil sample concentrations (ng/g) together with the child’s body weight (kg), 
estimated daily dust ingestion rate (g/day), estimated daily soil ingestion rate (g/day), and the 
estimated oral bioavailability. In CTEPP, the daily dust ingestion rates were calculated based on 
questionnaire responses related to specific activities of each child in the month prior to field 
sampling. These activities included pacifier use, teething, mouthing body parts, licking floors, 
and placing toys or other objects into the mouth. The daily soil ingestion rates were estimated 
based on how often a child played with sand/dirt and ate dirt, sand, or snow. Many of these 
parameters have very high uncertainty associated with them. The daily dust and soil ingestion 
rates were each estimated as 0.025, 0.050, or 0.100 g/day. The indirect exposure estimates, 
presented in Table 6.9, showed the following: 

• Indirect ingestion estimates for the permethrin isomers were much higher than for 
chlorpyrifos or diazinon, largely because permethrin was measured at much higher 
concentrations in floor dust (Figures 4.6 and 4.7). 

• The differences between NC and OH in mean permethrin concentrations in dust suggest 
potential regional differences in indirect ingestion. 


Table 6.9 The estimated exposures (ng/day) of NC and OH preschool children in the CTEPP 
study to chlorpyrifos, diazinon, and permethrin through indirect ingestion. 


Pesticide 

State 

N 

Mean 

SD 

GM 

GSD 

Min 

P25 

P50 

P75 

P95 

Max 

Chlorpyrifos 

NC 

117 

15.5 

29.0 

6.2 

1.3 

0.3 

2.8 

5.2 

14.8 

80.4 

233 

OH 

116 

27.8 

164 

3.0 

1.5 

0.2 

1.1 

2.7 

6.2 

33.5 

1570 

Diazinon 

NC 

118 

21.7 

81.9 

1.6 

2.0 

<MDL 

0.4 

1.0 

4.3 

150 

622 

OH 

116 

49.1 

367 

1.5 

1.9 

<MDL 

0.4 

1.0 

3.4 

45.3 

3800 

c/s-Permethrin 

NC 

120 

220 

670 

48.4 

1.6 

1.7 

17.1 

48.1 

113 

718 

4540 

OH 

116 

61.5 

139 

21.3 

1.4 

1.9 

7.8 

17.9 

52.7 

327 

1210 

/raHs-Permethrin 

NC 

120 

222 

698 

42.7 

1.7 

1.1 

11.9 

35.4 

119 

680 

4800 

OH 

102 

61.2 

153 

16.6 

1.5 

1.2 

5.3 

11.7 

45.9 

210 

1190 


<MDL, less than method detection limit 


103 























6.5 Indirect Ingestion: Summary 


As shown in the bulleted lists of observations from these laboratory and observational studies, 
progress has been achieved in identifying and quantifying a number of factors that are believed 
to potentially impact indirect ingestion among children. 

• Videotape analysis of children’s hand- and object-to-mouth contacts has provided 
evidence that hand-to-mouth activities were more frequent: among infants and toddlers 
than among older children, among girls than among boys, and at indoor locations than at 
outdoor locations. 

• Objects most commonly mouthed by preschoolers were identified as typically being toys 
and food-related items. 

• High chlorpyrifos loadings were measured on toy surfaces following routine residential 
application. 

• Fluorescent tracer experiments found that removal from skin (at very high tracer 
loadings) by mouthing was highly variable. Additional information is still needed on the 
fraction of residue transferred from the hands to mouth during typical mouthing events at 
dermal loading levels observed in field studies. 

• At high surface loadings, pesticide transfer to food was greater from hard, smooth 
surfaces than from carpet. 

• In homes with high surface pesticide residue loadings, residue concentrations in foods 
handled by children were often twice as high as concentrations in leftover unhandled 
foods. 

• The transfer of pesticide residues from surfaces to foods appears to be dependent on such 
factors as pesticide class, food type, contact duration, and applied force. 

• Indirect ingestion estimates for permethrin were much higher than for chlorpyrifos or 
diazinon, largely because permethrin was measured at much higher concentrations in 
floor dust. 


104 


7.0 DERMAL EXPOSURE MEASUREMENTS 

The ability to accurately estimate surface-to-skin transfer of contaminants from intermittent 
contacts remains a critical and missing link in pesticide exposure and risk assessments. For 
children’s exposures, transfer of chemicals from contaminated surfaces such as floors and 
furniture is potentially significant. Once on the skin, residues and contaminated particles can be 
transferred back to the contaminated surface during subsequent contact, lost by dislodgement or 
washing, or transferred into the body by percutaneous absorption or hand-to-mouth activity. A 
better understanding of the relevant factors influencing transfers from contaminated surfaces to 
skin and the resulting dermal loading will reduce uncertainty in exposure assessment. Areas of 
uncertainty with respect to dermal transfer are related to the important factors that impact 
transfer, whether or not a steady-state condition is reached, and the conditions that affect 
removal. Laboratory tests were conducted by NERL using nontoxic fluorescent tracers to 
evaluate significant transfer parameters. The results of these tests are described in this section 
(Section 7.1). 

Measurements of pesticide residues on children’s hands have been performed in a number of 
studies. Both hand wipe and hand rinse methods have been used. The collection efficiency of 
different wipe and rinse methods can be expected to differ, with an eight-fold difference reported 
between hand rinses and hand wipes in one study (Hore, 2003). Furthermore, differences in 
dermal exposure and dose due to free pesticide residue versus particle- (or dust-) bound 
pesticides may be important in interpreting the results. Results of wipes and rinses in selected 
studies are summarized in tables and figures presented below (in Section 7.2). 

An alternative approach for estimating dermal exposure is the cotton garment surrogate. Similar 
to the approach used for measuring occupational exposures to pesticides, cotton garments, which 
can consist of a bodysuit and/or socks, have been used in three studies that are reported below 
(Section 7.3). 

Important Factors Affecting Transfer 

Dermal exposure to surface residues is dependent on human activities that result in contact with 
surfaces and the physicochemical and mechanical mechanisms of transfer of residues from the 
surface to the skin. Several factors are commonly believed to affect transfer (Table 7.1). These 
factors can be grouped as characteristics of the surface (including contaminant loading, type of 
surface, and temperature), of the contaminant (including formulation, physical state, particle size, 
vapor pressure, viscosity, water solubility, lipophilicity, and being particle-bound), of the skin 
(including moistness and contact area), of contact (including duration, force, frequency, motion, 
and interval), and of protection measures (including clothing and hand washing). 

Many of these have previously been investigated, though not necessarily specific to pesticides 
and skin. Kissel et al. (1996) reported moisture content and particle sizes of soil to be significant 
factors affecting the process of adherence to skin. Rodes et al. (2001) reported that only about 
1/3 of the palm contacted surfaces during a press and that dust-to-skin transfer increased with 
hand dampness, decreased as surface roughness increased, and decreased with consecutive 
presses (requiring about 100 presses to reach equilibrium). Brouwer et al. (1999) reported that 


105 



whereas only 4-16% of the surface area of the palm of the hand is covered with a fluorescent 
tracer after one contact with a hard surface, about 40% becomes covered after twelve 
consecutive contacts. At least three studies have investigated the transfer of pesticides from 
surfaces to hands (measured using IPA wipes of hands.). Briefly, Lu and Fenske (1999) reported 
transfer of chlorpyrifos residues to hands to be 0.04 to 0.26% from carpets and 0.69% from 
furniture. Camann et al. (1996) examined transfer from nylon carpet to dry or moistened hands 
and reported transfers ranging from 0.7-1.3% for chlorpyrifos, 2.9-4.8% for pyrethrin I, and 
1.5-2.8% for piperonyl butoxide. Clothier (2000) examined transfer of the same residues from 
vinyl sheet flooring and reported transfers of 1.5% to dry and 4.4-5.2% to wet skin for 
chlorpyrifos, 3.6% (dry) and 8.9 - 11.9% (wet) for pyrethrin I, and 1.4% (dry) and 4.1-4.8% 

(wet) for piperonyl butoxide. 

7.1 Laboratory Fluorescent Measurement Studies 

Laboratory tests were performed to evaluate transfer efficiencies (TEs) of nontoxic fluorescent 
tracers (as surrogates for pesticide residues) from common household surfaces to hands (Cohen 
Hubal et al, 2005). The laboratory studies evaluated parameters affecting surface-to-hand 
transfer, including surface type, surface loading, contact motion, pressure, duration, and skin 
condition in two sets of experiments (Table 7.2). The data from the laboratory fluorescent 
measurement studies are presented in Tables 7.3 to 7.6 and Figures 7.1 and 7.2. 

• Tests comparing fluorescent tracers with pesticides (Figure 7.1) showed that the transfer 
of riboflavin to PUF rollers and Cl 8 disks is similar to that of chlorpyrifos, and that the 
transfer of Uvitex is similar to that of the pyrethroids permethrin and esfenvalerate. 

• Laboratory studies using fluorescent tracers riboflavin and Uvitex OB (Tables 7.3 to 7.6) 
indicated that tracer type, surface type, contact motion , and skin condition were all 
significant factors. Transfer was greater with laminate (over carpet), smudge (over 
press), and sticky skin (over moist or dry). Contact duration and pressure (force) were 
not important factors. 

• Comparison of “first contact” to “repeated contact” results (Table 7.4) suggests that the 
effect of surface type appears to diminish with repeated contact while the effect of skin 
condition (moist vs. dry) appears to increase with repeated contact. 

• Laboratory surface loadings (0.2 and 2.0 pg/cm 2 ) were much higher than the median 
values of 0.032 and 0.0014 pg/cm 2 measured by deposition coupons (Table 4.4) after 
crack and crevice application of chlorpyrifos in the Test House and CPPAES studies, 
respectively, 

• In the initial tracer experiments with high surface loadings, dermal loadings appear to 
reach a maximum by the fourth or fifth contact (data not presented), suggesting a 
saturation effect. In the follow-up experiments with lower surface loadings (Figure 7.2), 
dermal loadings appear to increase linearly through the seventh contact, suggesting that at 
lower surface loadings, more contacts may be required to reach steady state. 

• In “transfer off’ experiments described earlier (Section 6.2), the amount removed from 
fingers by mouthing was significantly different from zero in only half of the replicates. 


106 


Table 7.1 Factors commonly believed to affect dermal transfer. 


Category 

Parameter 

Source 

Surface 

Level of contamination 

Goede et al, 2003; This Report 

Type of surface: roughness, carpet vs. hard 
surface 

Brouwer et al., 1999; Rodes et al, 2001 

Contaminant 

Formulation 

Marquart et al., 2005 

Physical state: solid, liquid 

Marquart et al., 2005 

Particle characteristics: particle size 
distribution, moistness 

Kissel ef al., 1996 

Liquid characteristics: viscosity and related 
properties 

Marquart et al., 2005 

Physical properties of active ingredient: 
vapor pressure, water solubility, lipophilicity 

This Report 

Skin 

Moistness 

Camann et al., 1996; Clothier, 2000; Rodes et 
al., 2001; This Report 

Contact area 

Brouwer et al., 1999 

Contact 

Frequency: number of contacts or objects 

Brouwer et al., 1999; Rodes et al., 2001; This 
Report 

Interval between contacts 

Camann et al., 1996; 

Motion: press, smudge, drag 

Lu and Fenske, 1999; 

Protection 

Clothing: use, area covered, material 

Marquart et al., 2005 

Hand washing: frequency 

This Report 


Categories and parameters modified from Marquart et al., 2005. 


Table 7.2 Study parameters tested in surface-to-skin transfer experiments in the Characterizing 
Pesticide Residue Transfer Efficiencies study. 


Parameter 

Initial Experiments 

Refined Experiments a 

Tracer 

Riboflavin a 

Riboflavin b or Uvitex c 

Skin Condition 

Dry, Moist, or Sticky 

Dry or Moist 

Surface Type 

Carpet or Laminate 

Carpet or Laminate 

Surface Loading 

2 or 10 /zg/cm 2 

0.2 or 2 /zg/cm 2 

Contact Motion 

Press or Smudge 

Press or Smudge 

Contact Duration 

2 sec or 20 sec 

d 

Contact Pressure 

7 or 70 kg/cm 2 

— 

Contact Number 

Multiple 

Multiple 


a Refined experiments added Uvitex, reduced the loading levels, and reduced the number of parameters tested 
b Relatively water soluble 
c Relatively water insoluble 

d Blank cells indicate that parameter was not investigated in the study 


107 









































Table 7.3 Skin loadings (mean, standard deviation) measured following surface-to-skin transfer experiments (initial experiments). 
(Source: Cohen Hubal et al ., 2005.) 





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Contact 

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Pressure and duration not included in the follow-up experiments. 
Bold text indicates the parameter is statistically significant at p<0.05. 



































































































Table 7.6 Evidence of importance of factors tested across surface-to-skin transfer experiments. 


Parameter 

Initial Experiments 

Refined Experiments 

Tracer 

— 

•O 

Skin Condition 

•O 

• O 

Surface Type 

OO 

•O 

Surface Loading 

•o 

• • 

Contact Motion 

•• 

•O 

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OO 

— 

Contact Pressure 

OO 

— 

Contact Number 

•• 

• • 


— not tested 

OO not found to be significant 

•O mixed results or marginally significant at p<0.10 

• • significant at p<0.05 in all tests 


Transfer Efficiency (% Transfer) for Pesticides and Fluorescent Tracers 


100 


10 


1 - 


0.1 


0.01 


IBi. 




laminate 




carpet 


Transfer to Aqueous 
Wipe 


i 


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i;i : : : : % 

K I 




l 


lijui 

| 111 


fa 


H Diazinon 

□ Chlorpyrifos 

□ cis-Permethrin 

□ trans-Permethrin 

□ Esfenvalerate 

□ Riboflavin 

□ Uvitex OB 


^ \M— 

^ ^ — 
il= 


i i i 

laminate 

Li:itvfr/ivvCT 1 1 

carpet 

laminate 

liiii i;vftsx=i i i 

carpet 

Transfer to PUF Roller 

Transfer to Cl8 Press 



Disk (20 sec) 


Figure 7.1 Comparison of transfer efficiencies of fluorescent tracers and pesticides from laminate 
and carpet surfaces to various sampling media. 


110 
















































































































Loading by Contact No., Follow-Up Experiment 
Loading = high 
Analyte=Riboflavin 



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1 2 3 4 5 6 7 


Contact Number 


Figure 7.2 Hand loading by contact number, from the refined, follow-up experiments using 
Riboflavin (left panels) or Uvitex (right panels) with 2 /*g/cm 2 (high) (top panels) or 0.2 /*g/cm 2 
(low) (bottom panels) surface loadings. In these particular box-and-whisker plots, means and 
outliers (below 5 th or above 95 th percentiles) are represented by dots. 


Ill 






















































































7.2 Measurements of Pesticides on Hands by Wipe and Rinse Methods 

Measurements of pesticide residues on children’s hands have been performed in the MNCPES, 
CTEPP, CPPAES, PET, and DIYC studies. Collection efficiencies may vary among studies for a 
number of reasons. The method of wiping the surfaces of the hand may vary when performed by 
different researchers or by study participants themselves. Hand rinses may be more effective 
than hand wipes. Whether the method is a hand wipe or hand rinse, collection efficiency may 
differ for free pesticide residues versus particle-bound residue. Most of the data presented in this 
section were collected with hand wipes, except for MNCPES, in which rinses were collected. 
Both hand wipes and rinses were collected in CPPAES (with mean hand rinse to hand wipe 
ratios ranging from 4.1 to 7.8 by home). The amount of isopropanol used to collect the hand 
wipes/ rinses varied by study. A major issue associated with interpreting results of these 
measurements is the amount of a pesticide on the surface of skin that is never absorbed into the 
bloodstream. Solvents may extract some of pesticide from top layers of skin, though the extent 
of extraction will be a function of many factors including pesticide properties. 

Methods 

In CTEPP, hand wipe samples were collected from 257 preschool children using cotton sponges 
(SOF-WICK gauze pad; 4” x 4” - 3 ply; Johnson & Johnson) that were pre-cleaned and wetted 
with 2 mL of 75% isopropanol. The adult caregiver wiped the front and back of both hands of 
the child. A total of four wipe samples were collected over a 48-hr period (two per day, one 
before lunch and dinner, before washing hands). Samples were composited (combined) before 
analysis. The MNCPES hand rinses were collected at home from 102 children on day 1 of the 7- 
day monitoring period. A technician placed each of the child’s hands into a separate zip-closure 
bag containing 150 mL of isopropanol. Each hand’s sample was analyzed separately. The 
feasibility portion of the PET study collected hand wipes on multiple days from two children 
after a granular application of diazinon to the lawn by the homeowner. The cotton sponges 
(SOF-WICK gauze pad; 4” x 4” - 6 ply; Johnson & Johnson) were presoaked with 20 mL of 
isopropanol. Each child wiped the front and back of each hand. A total of five samples were 
collected from each child and each was analyzed separately. The CPPAES hand wipe samples 
were collected from 10 children on multiple days following a professional crack and crevice 
application of chlorpyrifos. Separate swabs that were wetted with an unreported amount of 
isopropanol were used to wipe the front and back of each hand. A small number of hand rinse 
samples were also collected. The DIYC study collected hand wipes on multiple days from three 
children after a crack and crevice application of diazinon. Each of two gauze pads, pre-wetted 
with 10 mL of isopropanol, was used to wipe both hands. The two wipes were extracted and 
analyzed as one sample. In all studies, the surface area of the children’s hands was measured. 

Results 

Table 7.7 summarizes the detection limits for the studies. The median and 95 th percentile 
concentrations are presented in Table 7.8. Individual hand loading measurements are presented 
in Tables 7.9. Relationships among populations and locations are illustrated in Figures 7.3 to 7.9 
and highlighted below. 


112 


• In the large observational field studies (Figure 7.3, Table 7.8), the loadings of 
chlorpyrifos on children’s hands measured with rinses in MNCPES were higher than the 
loadings measured with wipes in the other studies. 

• For all compounds, the hand loadings measured with hand wipes in the large 
observational field studies did not differ substantially (Figure 7.3, Table 7.8). 

• Median chlorpyrifos loadings on children’s hands (Figure 7.4) were much higher in 
CPPAES, where homes had recent crack and crevice applications, than in the large 
observational CTEPP and MNCPES studies. 

• Median diazinon loadings on children’s hands in the small, pilot-scale PET (lawn 
application) and DIYC (crack and crevice application) studies were much higher than in 
the large observational field study CTEPP (Figure 7.4). 

• Comparison of hand rinse and hand wipe samples collected from the same participants in 
CPPAES suggests that hand rinses were more effective at removing residues (Table 7.9). 

• Hand rinses may be more efficient than hand wipes at removing chlorpyrifos from the 
skin, but no information is available on which method better reflects the amount of 
pesticide that is either absorbed (dermal absorption) or potentially transferred to the 
mouth (indirect ingestion). 

i 

• In the CTEPP study, the median chlorpyrifos hand loadings were higher in NC than OH 
(at both homes and daycares), suggesting greater chlorpyrifos usage in NC than in OH. 
Permethrin levels were only slightly higher in NC than in OH (Figure 7.4). 

• At residential levels observed in CTEPP, median hand wipe-to-surface loading ratios 
reach or exceed 1 for the pesticides of interest (Figure 7.5). Please note that floor wipe 
loadings were measured using an IPA wipe method that was not as efficient as typical 
wipe methods (Section 4.4). 

• A strong relationship is evident in Figure 7.6 between CTEPP hand loadings measured at 
homes and those measured at daycares for chlorpyrifos (R 2 =0.47), diazinon (R 2 =0.44), 
and permethrin (R 2 =0.41). The relationship is weak for the degradation product TCPy 
(R 2 =0.03). 

• There was a strong relationship between children’s hand wipe loadings and adult hand 
wipe loadings for chlorpyrifos (R 2 =0.64; /3=0.77), diazinon (R 2 =0.77; /?=0.81), and 
permethrin (R 2 =0.49; (3=0.65 ) measured in CTEPP (Figure 7.7), despite largely different 
activity patterns between children and adults. 

• Based on regressions of CTEPP hand wipe measurements on either floor dust or floor 
wipe measurements for chlorpyrifos, diazinon, and permethrin (Figures 7.8 and 7.9), 
better relationships were observed between hand wipe and floor dust measurements 
(Figure 7.9) than between hand wipe and floor wipe measurements (Figure 7.8). 


113 


Table 7.7 Limits of detection (ng/cm 2 ) for dermal measurements by compound and study. 





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114 


Blank cells indicate that the pesticide was not measured in the study. 
CTEPP: h = home, d = daycare 








































Table 7.9 Comparison of chlorpyrifos and diazinon loadings (ng/cm 2 ) on children’s hands measured with hand rinse (HR) and hand 
wipe (HW) methods. 


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Participant 

Child 1 (4 yr) 

Child 2 (4 yr) 

Child 3 (4 yr) 

Child 4 (2 yr) 

Child 5 (4 yr) 

Child 6 (3 yr) 

Child 7 (3 yr) 

Child 8 (3 yr) 

Child 9 (4 yr) 

Child 10 (4 yr) 

Child 1 (6 yr) 

Child 2 (10 yr) 

Child 1 (2 yr) 

Child 2 (3 yr) 

Child 3 (1 yr) 

Study 



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115 








































CHLORPYRIFOS 
HAND LOADING (ng/cm2) 


DIAZINON 

HAND LOADING (ng/cm2) 



XXX MNCPES * * * CTEPP-NC HOME 

D □ □ CTEPP-NC DAYCARE O O O CTEPP-OH HOME 
AAA CTEPP-OH DAYCARE 


* * * CTEPP-NC HOME □ □ □ CTEPP-NC DAYCARE 

O O O CTEPP-OH HOME AAA CTEPP-OH DAYCARE 


CIS-PERMETHRIN 
HAND LOADING (ng/cm2) 


TRANS-PERMETHRIN 
HAND LOADING (ng/cm2) 



Percent 


* * * CTEPP-NC HOME ODD CTEPP-NC DAYCARE 

O O © CTEPP-OH HOME AAA CTEPP-OH DAYCARE 



Percent 


* * * CTEPP-NC HOME O Q □ CTEPP-NC DAYCARE 

POP CTEPP-OH HOME AAA CTEPP-OH DAYCARE 


TCPY 

HAND LOADING (ng/cm2) 


IMP 

HAND LOADING (ng/cm2) 



Figure 7.3 Log probability plots of hand loadings (MNCPES data are hand rinses, all others are 
hand wipes). 


116 




















































LOADING (rig/cm2) LOADING (ng/cm2) LOADING (ng/cm2) 


CHLORPYRIFOS 
HAND LOADING (ng/cm2) 


DIAZINON 

HAND LOADING (ng/cm2) 


100 


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MN NC HM NC DC OH HM OH DC CPPAES CPPAES NC HM 

HR HW 


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NC DC OH HM OH DC PET D1YC 


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HAND LOADING (ng/cm2) 


TRANS-PERMETHRIN 
HAND LOADING (ng/cm2) 


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HAND LOADING (ng/cm2) 


IMP 

HAND LOADING (ng/cm2) 




Figure 7.4 Comparison of hand loadings across studies. MNCPES data are hand rinses, 
CPPAES includes both hand rinses (HR) and hand wipes (HW), all others are hand wipes. 


117 









































































































RATIO 


Ratio of Handwipe Loading to Floor Wipe Loading 


Ratio of Handwipe Loading to Dust Loading 




Figure 7.5 Ratios of hand wipe loading to floor wipe loading (left panel) and hand wipe loading 
to dust loading (right panel) for pesticides in CTEPP. 


118 





















































CHLORPYRIFOS 


DIAZINON 



CIS-PERMEXHRIN 



CYFLUTHRIN 



TCPy 



Daycare Hand Loading (ng/cm2) 


IMP 



Doycore Hand Loading (ng/cm2) 


Figure 7.6 Relationship between children’s hand loadings measured at CTEPP homes and 
daycares. Coefficients of determination (R 2 ) and slopes (0) for log (base 10) values: chlorpyrifos 
(R^O.47; 0=0.91), diazinon (R 2 =0.44; 0=0.81), permethrin (R 2 =0.41; 0=0.72), cyfluthrin 
(R 2 =0.02; 0=0.19), TCPy (R 2 =0.03; 0=0.54), and IMP (R 2 =0.31; 0=0.54). 


119 















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Figure 7.7 Relationship between hand loadings among children and adults in CTEPP. 
Coefficients of determination (R 2 ) and slopes (/3) for log (base 10) values: chlorpyrifos (R 2 =0.64; 

0.77), diazinon (RM).77; 0=0.81), permethrin (R 2 =0.49; (3= 0.65), cyfluthrin (R 2 =0.20; 
0=0.61), TCPy (R 2 =0.30; 0=0.47), and IMP (R 2 =0.28; 13=0.63). 


120 














Com pound =Chlorpyrifos 


Compound=Diozinon 




Compound =c-Permethrin 


Compound=t-Permethrin 




Figure 7.8 Relationship between hand wipe measurements and floor wipe measurements in 
CTEPP. Coefficients of determination (R 2 ) and slopes (/ 3 ) for log (base 10) handwipe loadings 
regressed on log (base 10) floor wipe loadings are as follows: chlorpyrifos (R 2 =0.38; /?=0.64), 
diazinon (R 2 =0.46; /5=0.64), cw-permethrin (R 2 =0.54; /?=0.78), and /raw^-permethrin (R 2 =0.60; 
0=0.82). 


121 








Com po und =Chl orpy rifos 


Compound=Diozinon 



Floor Dust Looding (Home), ng/cm2 



Compound=c-Permethrin 


Compound=t-Permethrin 



Floor Dust Looding (Home), ng/cm2 



Figure 7.9 Relationship between hand wipe measurements and floor dust measurements in 
CTEPP. Coefficients of determination (R 2 ) and slopes (0) for log (base 10) handwipe loadings 
regressed on log (base 10) floor dust loadings are as follows: chlorpyrifos (R 2 =0.71; 0 = 0 . 78 ), 
diazinon (R 2 =0.69; 0=0.61), cw-permethrin (R 2 =0.72; 0=0.86), and rrans-permethrin (R 2 =0.76; 
0=0.88). 


122 









7.3 Measurements with Cotton Garments 

The US EPA Office of Pesticide Programs uses a transfer coefficient approach to assess 
children’s residential exposures to pesticides. The transfer coefficient approach was developed 
to assess occupational exposure in an agricultural setting, using empirically-derived dermal 
transfer coefficients to aggregate the mass transfer associated with a series of contacts with a 
contaminated medium. Dermal exposure sampling using a surrogate-skin technique such as a 
patch sampler or a whole-body garment sampler is conducted simultaneously with surface 
sampling for a specific activity, and a dermal transfer coefficient is then calculated. This 
transfer coefficient can then be used to estimate exposure for a similar activity by collecting only 
surface samples (Fenske, 1993), assuming that transfer is unidirectional (from surface to skin) 
and linear with time. Only limited research has been conducted to develop transfer coefficients 
for children in residential and daycare settings. Data were collected in the Daycare study (Cohen 
Hubal et al., 2006), JAX, and CPPAES with cotton garments. The data are presented in Tables 
7.10 to 7.12 and Figures 7.10 to 7.12. 

• Comparison of mean chlorpyrifos loadings on socks in JAX and CPPAES (Table 7.10) 
with surface loadings (Table 4.4) suggests that higher surface loadings do not necessarily 
correspond to higher sock loadings across studies. It also suggests that perhaps activity 
levels influence transfer. 

• The median chlorpyrifos loading on socks after a three-hour period in CPPAES was only 
about twice as high as the median loading after a one-hour period in the same 
environment (Table 7.10). This suggests that transfer to socks may not be linear with 
time, and again points towards the importance of activity levels. 

• Bodysuit esfenvalerate loadings in the Daycare study were typically higher in the 
mornings, corresponding to higher group activity levels at that time (Figure 7.10). 
Depletion of surface loadings by morning activities is unlikely but was not tested. 

• Multiple regression analysis of Daycare data suggests that body section (arms, legs, lower 
torso, and upper torso), relative activity level, and age group are all important predictors 
of bodysuit loadings (Table 7.11). 

• The statistical significance of activity (Table 7.11), even when controlling for age group, 
suggests that activity level within age groups may be as important as age-related 
differences. 

• The between- and within-person variability (GSD) in dermal exposures in the daycare 
setting (Table 7.12) is similar to what has been reported in agricultural/industrial settings. 

• High within-person variability (compared to between-person variability) in cotton 
garment loadings (Table 7.12) suggests that factors related to changing environmental 
conditions and to differences in structured activities may be more important than child- 
specific characteristics. 

• The relative standard deviations (%) of esfenvalerate loadings on cotton garment sections 
(Figure 7.11) were typically higher among infants during the morning sessions and 
among preschoolers during the afternoon sessions. This suggests that the structured 


123 


activities may have had a stronger influence on the observed variability than surface 
loadings in the respective rooms. 

• Infants had 1.5 times as many hand wipe values (36%) above the MDL as preschool 
children (24%), consistent with the higher bodysuit loadings, perhaps reflecting greater 
contact with the floor surface. Figure 7.12 illustrates that among the hand wipes above 
the MDL, infants typically had higher loadings, with greater variability. 

• The association between hand wipe samples above the limit of detection and average 
body suit loadings was statistically significant (Spearman rho = 0.54, p < 0.05, data not 
presented). 


124 


Table 7.10 Pesticide loading (ng/cm 2 ) on cotton garments worn by children in three studies. 


Study 

Compound 

Garment 

Type/Section 

Age 

N 

% Det 

MDL 

Mean 

SD 

P50 

P95 

Daycare 

Esfenvalerate 

Arms 

9-13 mo 

26 

92 

0.01 

0.12 

0.18 

0.06 

0.42 

24-38 mo 

28 

100 

0.01 

0.1 

0.09 

0.07 

0.23 

Legs 

9-13 mo 

26 

100 

0.01 

0.27 

0.21 

0.22 

0.75 

24-38 mo 

28 

93 

0.01 

0.2 

0.41 

0.1 

0.46 

Lower Torso 

9-13 mo 

26 

100 

0.01 

0.28 

0.23 

0.18 

0.73 

24-38 mo 

28 

100 

0.01 

0.2 

0.18 

0.12 

0.52 

Upper Torso 

9-13 mo 

26 

96 

0.01 

0.05 

0.05 

0.03 

0.12 

24-38 mo 

28 

100 

0.01 

0.09 

0.13 

0.05 

0.16 

CPPAES 

Chlorpyrifos 

Bottom 

2-5 yr 

7 

100 

0.01 

0.58 

0.37 

0.7 

1.0 

Knee 

2-5 yr 

14 

100 

0.01 

0.62 

0.4 

0.7 

1.2 

Leg 

2-5 yr 

14 

100 

0.01 

0.38 

0.27 

0.45 

0.8 

Sock (1 hr) 

2-5 yr 

14 

100 

0.01 

8.6 

14 

3.5 

53 

Sock (3 hr) 

2-5 yr 

14 

100 

0.01 

10.8 

13 

7.6 

30 

JAX 

Chlorpyrifos 

Sock 

4-6 yr 

9 

100 

0.4 

2.3 

1.3 

2.2 

5.1 

Diazinon 

Sock 

4-6 yr 

9 

33 

0.08 

NC 

NC 

<0.08 

1.8 

Esfenvalerate 

Sock 

4-6 yr 

9 

22 

0.28 

NC 

NC 

<0.28 

2.6 

Cyfluthrin 

Sock 

4-6 yr 

9 

0 

0.24 

NC 

NC 

<0.24 

<0.24 

c/s-Permethrin 

Sock 

4-6 yr 

9 

44 

0.8 

NC 

NC 

<0.8 

128 

/raws-Permethrin 

Sock 

4-6 yr 

9 

100 

0.2 

23.6 

59 

1.44 

180 

CHAMACOS 

Chlorpyrifos 

Union Suit 

6-10 mo 

10 

100 

0.001 

0.026 

0.025 

0.019 

0.095 

21-27 mo 

10 

100 

0.001 

0.016 

0.008 

0.015 

0.025 

Sock 

6-10 mo 

9 

89 

0.05 

0.18 

0.10 

0.17 

0.37 

21-27 mo 

10 

90 

0.05 

0.28 

0.18 

0.24 

0.64 

Diazinon 

Union Suit 

6-10 mo 

10 

100 

0.001 

0.017 

0.012 

0.014 

0.043 

21-27 mo 

10 

100 

0.001 

0.052 

0.13 

0.009 

0.42 

Sock 

6-10 mo 

9 

78 

0.02 

0.099 

0.094 

0.070 

0.29 

21-27 mo 

10 

90 

0.02 

0.50 

1.1 

0.13 

3.5 

Esfenvalerate 

Union Suit 

6-10 mo 

10 

10 

0.02 

NC 

NC 

<0.02 

0.038 

21-27 mo 

10 

10 

0.01 

NC 

NC 

<0.01 

0.047 

Sock 

6-10 mo 

9 

11 

0.25 

NC 

NC 

<0.25 

1.9 

21-27 mo 

10 

10 

0.25 

NC 

NC 

<0.25 

2.3 

Cyfluthrin 

Union Suit 

6-10 mo 

10 

10 

0.07 

NC 

NC 

<0.07 

1.1 

21-27 mo 

10 

0 

0.04 

NC 

NC 

<0.04 

<0.04 

Sock 

6-10 mo 

9 

0 

2.5 

NC 

NC 

<2.5 

<2.5 

21-27 mo 

10 

10 

2.5 

NC 

NC 

<2.5 

14 

m-Permethrin 

Union Suit 

6-10 mo 

10 

100 

0.001 

0.19 

0.11 

0.18 

0.41 

21-27 mo 

10 

100 

0.001 

0.96 

2.4 

0.16 

7.9 

Sock 

6-10 mo 

9 

100 

0.02 

2.0 

2.8 

1.1 

8.7 

21-27 mo 

10 

100 

0.02 

6.2 

13 

1.8 

43 

/raws-Permethrin 

Union Suit 

6-10 mo 

10 

100 

0.001 

0.18 

0.35 

0.088 

1.2 

21-27 mo 

10 

100 

0.001 

0.96 

2.6 

0.059 

8.4 

Sock 

6-10 mo 

9 

100 

0.02 

2.6 

2.4 

1.9 

7.7 

21-27 mo 

10 

100 

0.02 

10 

22 

2.0 

71 


NC, Not calculated 


125 


































































Table 7.11 Results of multiple linear regression modeling of measured bodysuit pesticide loading 
(ng/cm 2 /sec) from data collected in the daycare study. 


Effect 

Level 

Estimate 

p-Value 

Intercept 

intercept 

-1.43 

<0.0001 

Bodysuit Section 

arms 

0.46 

<0.0001 

legs 

1.05 

lower torso 

1.35 

upper torso 

0 

Visit 

first 

0.87 

0.0006 

second 

0.31 

third 

0 

Session 

am 

0.44 

0.0006 

pm 

0 

Activity Level 

high 

1.36 

<0.0001 

middle 

0.65 

low 

0 

Classroom 

infant 

0.38 

0.0386 

preschool 

0 


Table 7.12 Estimates of between- and within-person variability for loading on individual 
bodysuit sections. 


Statistic 

Arms 

Upper 

Legs 

Lower 

Between-person variance (logged) 

0.26 

0.04 

0.67 

0.37 

Within-person variance (logged) 

0.76 

0.76 

1.02 

0.59 

Intraclass Correlation Coefficient 

0.25 

0.05 

0.40 

0.39 

GSD, between 

1.7 

1.2 

2.3 

1.8 

GSD, within 

2.4 

2.4 

2.7 

2.2 


126 































Loading (ng/cm2) Loading (ng/cm2) 


ARMS 


UPPER TORSO 


10 - 


0.1 


0.01 - 


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18 Jul 2001 1 22 Aug 2001 119 Sep 2001 


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cn 

c 

O' 

c 

ID 

O 

o 


10 


1 


0.1 


0.01 



am pm am pm am pm 


am pm am pm am pm 


Figure 7.10 Bodysuit section loadings (ng/cm 2 ) by monitoring period from the Daycare study. 


127 




















































































































































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Visit No. 1 


□ Infants 
Preschoolers 



Visit No. 2 



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Visit No. 3 


Figure 7.11 Relative standard deviations of esfenvalerate loadings on cotton garment sections 
among infants and preschoolers in the Daycare study. 


N 

E 


o 

o> 

c 

d> 

Q. 


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T3 

C 

<0 

X 


0.12 


0.10 


0.08 


0.06 


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Rank (Highest=1) 

Figure 7.12 Handwipe loadings (ng/cm 2 ) above method detection limit among infants and 
preschoolers in the Daycare study. Values are sorted in descending order, illustrating that the 
highest loadings were typically from infants and the lowest typically from preschoolers. 


128 






































































































































































8.0 URINARY BIOMARKER MEASUREMENTS 


Biological markers are indicators of the actual body burden of a chemical. As such, they reflect 
all routes of exposure, as well as inter-individual differences in absorption and metabolism. 
Moreover, they are often more directly related to potential adverse health effects than the 
external concentrations (Lowry, 1986: Hulka and Margolin, 1992). In human observational 
measurement studies involving young children, urine is the primary vehicle for biomonitoring. 
Urine is advantageous over blood because of its noninvasiveness, ease of collection, and large 
available quantity. Urinary biomarkers, however, also have disadvantages related to 
uncertainties in the fraction of the absorbed compound that is eliminated and in the precision of 
the measurements. 

The relationship between a biological marker and external exposure is influenced by factors 
related both to the environment and to human physiology. Factors related to the environment 
include spatial and temporal variability in exposure concentrations (as discussed in earlier 
chapters of this report) and effects of the presence of other chemicals (Coble et al, 2005). 

Factors related to human physiology include differences, both over time and across individuals, 
in the rates of absorption, distribution, metabolism, and excretion (Droz, 1989). When biological 
monitoring and exposure monitoring are used together, the relationship between the two may be 
evaluated to investigate the relative contribution of the various exposure routes. 

Evaluating the relative contribution of exposure routes to aggregate intake is subject to error 
related to estimates of exposure and of aggregate intake. Issues related to route-specific 
exposure estimates have been discussed earlier. Dependable information on the toxicokinetics 
(absorption, distribution, metabolism, and excretion) of a compound are necessary for reliable 
estimates of aggregate intake, whether those estimates are derived from the sum of route-specific 
absorption estimates or from excreted biomarker levels. To accurately estimate aggregate intake 
from excreted biomarker levels, urinary biomarker output rates must be calculated from the 
biomarker levels. Such calculations require information on the entire urine volume and elapsed 
time since previous void - information that has rarely been collected in field studies. 

8.1 Toxicokinetics of Organophosphate and Pyrethroid Pesticides 

Some understanding of organophosphate and pyrethroid pesticide toxicokinetics is necessary to 
meaningfully compare the environmental and dietary concentrations presented in the previous 
chapters with the urinary biomarker concentrations presented in this chapter. Despite extensive 
usage, remarkably little is available from the scientific literature on kinetic parameters in 
humans. Parameters reported for absorption of parent compounds and elimination of urinary 
metabolites following pesticide exposure are summarized in Table 8.1. 

Absorption 

Inhalation studies with a variety of gases have shown that even the most efficiently absorbed low 
molecular weight, highly water soluble compounds rarely exceed 70% uptake. No studies 
reporting the fraction of organophosphate pesticides absorbed through inhalation were found, but 


129 


Leng et al (1997) reported that only about 16% of the pyrethroid cyfluthrin was absorbed 
through inhalation. 

The importance of the dietary contribution to aggregate exposure among infants and young 
children is well known (NRC, 1993), but few studies have investigated what fraction of ingested 
pesticide residue is absorbed. For organophosphates, Nolan et al (1984) estimated 70% 
absorption of chlorpyrifos based on urinary 3,5,6-trichloro-2-pyridinol (TCPy), whereas others 
estimated 60% to 93% absorption based on dialkylphosphate (DAP) metabolites (Garfitt et al., 
2002; Griffin et al ., 1999). Diet reportedly affects absorption (Timchalk et al ., 2002). As for 
pyrethroids, Woollen et al (1992) estimated that 27-57% of cypermethrin was absorbed, while 
Eadsforth and colleagues (1983; 1988) estimated 45-49% and 72-78% for the cis and trans 
isomers, respectively. 

Dermal absorption is typically low due to loss by washing, evaporation, or exfoliation (Feldmann 
and Maibach, 1974). For organophosphate pesticides, absorption of chlorpyrifos was estimated, 
based on its primary metabolite TCPy, to be 1.28% of an applied dose of 4 mg/cm 2 (over 12-20 
hr) (Nolan et al., 1984), and 1.2% and 4.3% of applied doses of 0.15 and 0.05 mg/cm 2 (over 4 
hr), respectively (Meuling et al., 2005). Absorption of both chlorpyrifos and diazinon was 
estimated to be about 1% of applied doses of about 0.4 and 1.3 mg/cm 2 (over 8 hr), respectively, 
based on DAP metabolites (Griffin et al, 1999; Garfitt et al., 2002). The percent that is 
absorbed increases as the applied dose (per cm 2 ) decreases. Large differences have been 
reported by anatomical area (Maibach et al, 1971) and among individuals (Feldmann and 
Maibach, 1974). For pyrethroids, Bartelt and Hubbell (1987) found only about 2% of applied 
permethrin to be absorbed within 24 h. Wester et al (1994) observed that approximately 2% 
(forearm) and 7.5% (scalp) of radiolabeled pyrethrin was absorbed. The ATSDR (2001) has 
concluded that for pyrethroids in general, < 2% of the applied dermal dose is absorbed, at a rate 
much slower than that by the oral or inhaled routes. 

Due to the paucity of available information on absorption from human studies, simple default 
values based on human studies, animal studies, and conservative assumptions are often required. 
For small children (ages 1-6) the following route-specific absorption is often assumed: 50-100% 
for inhalation, 50% for ingestion, and 1-3% for dermal. In addition, a daily intake of 100 mg of 
house dust is assumed for indirect ingestion. These absorption assumptions are a source of 
substantial uncertainty in route-specific intake estimates. In fact, since dermal absorption 
increases with decreasing dermal loadings (as demonstrated above with organophosphates), 
default assumptions of less than 3% for dermal absorption may underestimate absorption at the 
very low levels measured in field studies 

Distribution and Metabolism 

Once in the bloodstream, organophosphate or pyrethroid pesticides are rapidly distributed and 
metabolized. A typical organophosphate (OP) pesticide is composed of a dialkyl (either 
dimethyl or diethyl) phosphate moiety and an organic group. Hydrolytic cleavage of the ester 
bond yields one dialkylphosphate (DAP) metabolite and one organic group moiety (Barr et al, 
2004). Dimethyl OPs (including malathion, phosmet, and azinphos-methyl) produce dimethyl 
metabolites and diethyl OPs (including chlorpyrifos and diazinon) produce diethyl metabolites 


130 


(Aprea et al, 2002). The organic group metabolites, including 2-isopropyl-6-methyl-4- 
pyrimidinol (IMPy) for diazinon and 3,5,6-trichloro-2-pyridinol (TCPy) for chlorpyrifos, are 
considered to be semi-specific. 

Pyrethroids are esters of chrysanthemic acid and benzyl alcohols. Hydrolytic cleavage of the 
ester bond yields a benzoic acid and a chrysanthemic acid derivative. The 3-phenoxybenzoic 
acid (3-PBA) metabolite is common to 10 of the 18 pyrethroids registered in the United States 
including permethrin, cypermethrin, deltamethrin, esfenvalerate (Baker et al., 2004). Other 
benzoic acid metabolites analogous to 3-PBA are more specific and include 4-fluoro-3- 
phenoxybenzoic acid (4F3PBA) from cyfluthrin and 2-methyl-3-phenylbenzoic acid (MPA) 
from bifenthnn. These are not necessarily terminal metabolites; for example, as much as 38% of 
3-PBA has been reported by Woollen et al. (1992) to undergo further oxidation to 3-(4'- 
hydroxyphenoxy) benzoic acid (40H3PBA). The chrysanthemic acid derivative cis- 2,2- 
dibromovinyl-2,2-dimethyl-cyclopropane-l-carboxylic acid (DBCA) is specific to deltamethrin 
while the cis- and trans- isomers of 2,2-dichlorovinyl-2,2-dimethyl- cyclopropane-1 -carboxylic 
acid (DCCA) are common to permethrin, cypermethrin, and cyfluthrin. 

Excretion 

Both the OPs and the pyrethroids are rapidly eliminated in urine. Elimination appears to follow 
first-order kinetics, with elimination half-times in humans ranging from 2 to 41 hours for OPs 
and from 6.4 to 16.5 hours for pyrethroids, depending on both the compound and the route of 
exposure (ATSDR, 2001; Garfitt et al ., 2002; Meuling et al ., 2005). The elimination half-life of 
about 8 hours reported for 3-PBA among workers exposed to cypermethrin (Kuhn et al ., 1999) 
suggests that 88% of the metabolite is excreted within the first 24 hours following exposure. 

Route-specific differences in the peak excretion of urinary OP pesticide metabolites have been 
reported (Griffin et al ., 1999; Garfitt et al ., 2002; Meuling et al ., 2005). Peak excretion is 
observed to occur 6 to 24 hours later when absorption is by the dermal route compared to when 
absorption is by the oral route, largely because of route-specific differences in absorption. Peak 
excretion may occur as late as 48 hours following dermal exposure, as observed among 
volunteers performing scripted “Jazzercise” activities (Krieger et al ., 2000). Extended peak 
excretion times suggest that chlorpyrifos may be retained by the skin and may remain 
systemically available for prolonged periods (Meuling et al ., 2005) 

While the above toxicokinetic studies evaluate excreted mass or mass rates, our past field studies 
have largely evaluated only biomarker concentrations. In the future, all studies should include 
information on void volumes and times to allow excreted mass to be calculated. Relevant 
transformations can be found in Rigas et al. (2001) and are currently incorporated in the SHEDS 
model. 


131 


Table 8.1 Absorption and elimination characteristics for pesticides and urinary biomarkers of pesticide exposure. 


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8.2 Measurements of Pesticide Metabolites in Urine 

Urinary biomarkers were measured in several large-scale and pilot-scale children’s observational 
measurement studies described in Table 8.2. These include the MNCPES, CTEPP, NHEXAS- 
AZ, CPPAES, JAX, CHAMACOS, PET, and DIYC studies. All urine samples were collected 
exclusively at the children’s homes except for the CTEPP study, in which urine samples were 
also collected at daycare centers. Urine collection followed outdoor turf applications in the PET 
study and routine professional indoor applications in the DIYC and CPPAES studies. 

Spot urine samples, mainly first morning voids, were collected using age-appropriate methods 
including under-toilet seat bonnets (CTEPP, PET), collection cup (NHEXAS-AZ, MNCPES), 
diaper insert (DIYC), and “potty chair” (CPPAES). Table 8.3 presents selected organophosphate 
(OP) and pyrethroid metabolites that were measured in the children’s urine samples in multiple 
studies. The pesticide metabolites are 3,5,6-trichloro-2-pyridinol (TCPy), 2-isopropyl-6-methyl- 
4-pyrimidinol (IMP), and 3-phenoxybenzoic acid (3-PBA). 

Sample collection was performed by the children’s caregivers following protocols provided by 
the investigators. Chemical analysis of urinary metabolites in nearly all included studies was 
performed by the National Center for Environmental Health of the Centers for Disease Control 
and Prevention in Atlanta, GA, using validated tandem mass spectroscopy techniques (Baker et 
al, 2000; Baker et al, 2004; Beeson et al, 1999; Hill et al, 1995). Chemical analysis for the 
CTEPP study was performed by Battelle Institute using validated gas chromatography/mass 
spectroscopy techniques. 

Limits of detection for each pesticide metabolite are given by study in Table 8.4. Detection 
frequencies are provided in Figure 8.1. Concentrations for the median and 95 th percentiles for 
each urinary metabolite are presented by study in Table 8.5. Figure 8.2 shows the log probability 
plots of urinary TCPy and 3-PBA concentrations for children across large observational field 
studies. Figure 8.3 presents the box-and-whisker plots that graphically depict the urinary TCPy 
and 3-PBA concentrations for both the large-scale and pilot-scale children’s observational 
measurement studies. 

The National Health and Nutrition Examination Survey (NHANES) includes an ongoing 
assessment of the exposure of the U.S. population to environmental chemicals through the 
measurement of biomarkers. Spot measurements of urinary pesticide biomarkers among children 
6 to 12 years old from both the 1999-2000 and the 2001-2002 cycles are included for comparison 
with results from our studies. Please note that NHANES does not report results by region or by 
season. 


• The chlorpyrifos metabolite TCPy was detected in over 90% of the children’s urine 
samples in all listed studies. The pyrethroid metabolite 3-PBA was detected in over 60% 
of the CTEPP-OH samples and over 90% of the JAX samples (Figure 8.1). 

• The urinary TCPy concentrations were at least an order of magnitude higher than the 
urinary 3-PBA concentrations across studies (Figure 8.2). 


133 


• There is virtually no difference in urinary TCPy concentrations measured in CTEPP NC 
and OH, but the concentrations from Minnesota and Arizona are substantially higher 
(Figure 8.2, all unweighted). Higher levels in MNCPES and NHEXAS-AZ may reflect 
intentional oversampling of pesticide-using households in MNCPES, and greater use of 
chlorpyrifos at the time that MNCPES and NHEXAS-AZ were conducted. 

• Compared to values for children under 12 years old collected in the 1999-2002 NHANES 
(Figure 8.2), the median TCPy values were higher in all of our studies, but the 95 th 
percentile values were only higher for MNCPES. 

• The children in JAX had levels of 3-PBA that were at least seven times higher than those 
of children in CTEPP-OH (Figure 8.3). All urine data from JAX participants suggest that 
JAX is a high pesticide usage area. 

• The median 3-PBA value in CTEPP (0.3 ng/mL) was similar to NHANES (0.3 ng/mL), 
but the median JAX value (2.2 ng/mL) was much higher (Figure 8.3). 

• Levels of IMP were about an order of magnitude higher in DIYC compared to PET or 
NHANES (Figure 8.3). 

• The median urinary TCPy concentration was the highest for the NHEXAS-AZ and JAX 
studies and the lowest for the CTEPP-NC and CTEPP-OH studies (Table 8.5). 

• In the CPPAES study, the intensity of the crack and crevice applications of chlorpyrifos 
was described as either high (n = 7) or low (n = 3), with mean air concentrations resulting 
from “high” applications five orders of magnitude higher than those from “low” 
applications. Figure 8.4 shows that the urinary TCPy concentrations over time were not 
much different for the children in the high versus low application groups. 

• For children in the “high” application group in CPPAES, the median urinary TCPy 
concentration one day before application of chlorpyrifos was higher than on the first two 
days following application (Figure 8.4). Crack and crevice applications of chlorpyrifos at 
these homes did not substantially increase the children’s urinary TCPy concentrations. 

• The concentration-time profiles for urinary TCPy levels in CPPAES did not mirror the 
environmental concentration time profiles (Figure 8.5). 


134 


Table 8.2 Summary of the children’s urinary biomarker collection methods. 



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Analytes relevant to interstudy comparison. Most studies included additional metabolites. 




















Table 8.3 Urinary metabolites of organophosphate and pyrethroid pesticides measured in the 
children’s observational measurement studies. 


Metabolite 

Parent Compound 

3,5,6-Trichloro-2-pyridinol (TCPy) 

Chlorpyrifos a 

2-Isopropyl-6-methyl-4-pyrimidinol (IMP) 

Diazinon 

3-Phenoxybenzoic acid (3-PBA) 

Permethrin b 


a TCPy is also a metabolite of chlorpyrifos-methyl, which may occur in children’s diet. 
b Several other pyrethroids are metabolized into 3-PBA including cypermethrin, deltamethrin, fenvalerate, 
fluvalinate, permethrin, sumithrin. 


Table 8.4 Limits of detection (ng/mL) for each pesticide metabolite measured in the children’s 
urine samples by study. 


Study 

TCPy 

IMP 

3-PBA 

NHEXAS-AZ 

1.0 

NA 

NA 

MNCPES 

1.4 

NA 

NA 

CTEPP-NC 

1.0 

NA 

NA 

CTEPP-OH 

1.0 

NA 

0.2 

JAX 

0.4 

2.0 

0.5 

CPPAES 

1.0 

NA 

NA 

PET 

NA 

0.3 

NA 

DIYC 

NA 

1.0 

NA 


NA, Not Applicable. 


Table 8.5 Median and 95 percentile values (ng/mL) for the pesticide metabolites TCPy, IMP, 
and 3-PBA measured in the children’s urine samples by study. 


Study 

TCPy 

IMP 

3-PBA 

P50 

P95 

P50 

P95 

P50 

P95 

NHEXAS-AZ 

12.0 

26.0 

NA 

NA 

NA 

NA 

MNCPES 

7.2 

23.0 

NA 

NA 

NA 

NA 

CTEPP-NC 

5.3 

15.5 

NA 

NA 

NA 

NA 

CTEPP-OH 

5.1 

12.3 

NA 

NA 

0.3 

1.8 

JAX 

9.8 

21.2 

<MDL 

<MDL 

2.2 

98.7 

CPPAES 

7.7 

18.0 

NA 

NA 

NA 

NA 

PET 

NA 

NA 

0.71 

6.58 

NA 

NA 

DIYC 

NA | NA 

7.1 

27.0 

NA 

NA 


NA, Not Applicable. 


136 






































Detection Frequency in Urine 




IMP 



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EbB MNCPES 
CPPAES 




CTEPP-OH 

PET 


^3CTEPP-NC 

DIYC 


Figure 8.1 Detection frequencies of pesticide metabolites in the children’s urines samples by 
study. 


137 





































































































TCPY 

URINE (ng/ml) 



Percent 


+ + -4- NHEXAS-AZ XXX MNCPES 

Y Y Y CTEPP-NC Z Z Z CTEPP-OH 

0 Q G NHANES 


3-PBA 

URINE (ng/ml) 



IMP 

URINE (ng/ml) 



Figure 8.2 Log probability plots of urinary TCPy, 3-PBA, and IMP concentrations across large 
observational field studies. NHANES results are included for comparison. 


138 
























CONCENTRATION (ng/ml) CONCENTRATION (ng/ml) 


TCPY 

URINE (ng/ml) 


3-PBA 

URINE (ng/ml) 



1000 


100 


10 


1 1 


0.1 1 


0.01 - 



- 1 - 1 - 1 - 1 — 

CTEPP-OH JAX-SCR JAX-EXPO N HANES 


IMP 

URINE (ng/ml) 



Figure 8.3 Box-and-whisker plots comparing the urinary TCPy and 3-PBA concentrations across 
studies. 

































LOW 


High 


CL. 


20 - 
1« : 
16- 
14 - 
12 - 
10 - 
8* 
6 - 
4- 
2 


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1 






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Figure 8.4 Urinary TCPy concentrations (ng/mL) over time for the children in the high and low 
application groups in CPPAES. 



Figure 8.5 Time profiles for chlorpyrifos in environmental media and TCPy concentrations in 
urine for all children in the CPPAES. 


140 











































































8.3 Temporal Variability in Biomarker Measurements 

In the CTEPP study, the children’s spot urine samples (up to six per child) were analyzed 
separately for pesticide metabolites if the participants reported that a pesticide had been used in 
their homes within seven days of field monitoring. Figure 8.6 shows the variability of urinary 
TCPy concentrations in the children’s urine samples over a 48-h period. 

Intraclass correlation coefficients (ICCs) for urinary TCPy and 3-PBA concentrations in NC and 
OH children in the CTEPP study are provided in Table 8.6. The between and within-person 
geometric standard deviations (GSDs) for logged urinary concentrations of TCPy and 3-PBA for 
the NC and OH children in the CTEPP study are given in Table 8.7. Concentration-time profiles 
for TCPy and 3-PBA among CTEPP children are provided in Figure 8.6 and for IMP among 
PET study children in Figure 8.7. 

• Relatively low ICCs (Table 8.6) indicate that a single measurement may not adequately 
represent the mean of the 48-hr sampling period for 3-PBA among adults and TCPy 
among children. Consistency of urinary metabolite concentrations over even short 
periods of time appears to be dependent on both the metabolite and the study population. 

• Within-person GSDs are equal to or nearly equal to between-person GSDs for both TCPy 
and 3-PBA in urine measured in CTEPP (Table 8.7). This indicates that a single spot 
urine measurement is not sufficient to differentiate among children over a 48-hr time 
frame. 

• Spot urine measurements over 48 hours among CTEPP participants reporting recent 
pesticide applications show large sample-to-sample variability and large differences 
among individuals (Figure 8.6). 

• Adjustment of urinary metabolite values by specific gravity did not meaningfully reduce 
within-person variability of TCPy (Figure 8.6). 

• While no statistically significant difference was observed between pre- and post¬ 
application urinary IMP concentrations in the PET study, the time-concentration profile 
clearly shows an observable decay in children’s urinary biomarker concentrations in the 
eight days following the outdoor lawn application (Figure 8.7). The pattern among adults 
is not consistent with that among children. 

• Comparing first morning voids (FMV) to other spot samples collected among a 
subsample of CTEPP children (data not presented), the median concentration in FMV is 
substantially (43%) higher than the median of the non-FMV samples for TCPy, and 
slightly (35%) higher for 3-PBA, due to longer urine accumulation time in the bladder. 

• In CHAMACOS, concentrations in overnight diapers were compared to concentrations in 
spot samples (Bradman et al ., 2006; data not presented). In all cases, diethyl phosphates 
were lower in overnight diaper samples than in spot samples, while for toddlers dimethyl 
phosphates were higher in overnight diaper samples. Median total DAP concentrations 
for all children were higher in the overnight samples compared to the spot samples (140 
vs. 100 nmol/1), but the differences were not statistically significant (Wilcoxon test). 


141 


• Spearman correlations were calculated for CHAMACOS spot and overnight samples by 
age (Bradman et al ., 2006). Spot and overnight urine concentrations were significantly 
correlated in CHAMACOS (Bradman et al ., 2006): dimethyl phosphate (Spearman 
rho=0.53; p=0.02), diethyl phosphate (Spearman rho=0.48; p=0.03), and total DAP 
metabolites (Spearman rho=0.57; p=0.009). 


Table 8.6 Intraclass correlation coefficients (ICC) for logged CTEPP urinary metabolites. a 


Metabolite 

NC Children 

OH Children 

3-PBA 

_ b 

0.70 

TCPy 

0.65 

0.48 


a An ICC of 0.80 indicates that a single measurement reliably represents the average of a set of measurements. 
b -- = no data. 


Table 8.7 Between- and within-person geometric standard deviations (GSDs) for logged urinary 
concentrations from children in the CTEPP study. 


Metabolite 

Measure 

NC Children 

OH Children 

3-PBA 

Between-person GSD 

a 

1.5 


Within-person GSD 

— 

1.2 

TCPy 

Between-person GSD 

1.5 

1.5 


Within-person GSD 

1.3 

1.5 


- a -- = no data. 


142 















NC 


OH 




NC 


OH 




Time (Hours) 


Figure 8.6 Concentration versus time plots for urinary TCPy measurements among CTEPP-NC 
and CTEPP-OH participants reporting a recent pesticide application. Urines in panels A and B 
are without adjustment. Urines in panels C and D are adjusted by specific gravity. Note that not 
all voids within the 48 hour period were collected. 


Children's IMP (mean +/- std err) Adults' IMP (mean +/- std err) 




Figure 8.7 Time-concentration profile for urinary IMP measurements among child and adult PET 
study participants following an outdoor granular turf pesticide application. 


143 
































8.4 Urine and Creatinine Excretion among Children 

Urine output varies with water intake, urea, salt, specific gravity, and osmolality (Wessels et al, 
2003). Consequently, the concentration of metabolites in spot urine samples may vary, even if 
the internal dose remains constant. Since collecting 24-h urine samples from children is often 
impractical, spot urine samples are commonly collected and normalized using creatinine (CRE) 
concentration. However, CRE yield has been shown to be variable among children (Freeman et 
al , 1995; O’Rourke et al , 2000). Furthermore, because CRE excretion is dependent upon 
muscle mass, children inherently excrete less CRE than adults. This makes comparisons 
between CRE-adjusted adult and children urinary biomarker concentrations subject to error due 
to “over-correction” of children’s samples. Age-dependent differences in daily creatinine 
clearance must also be considered when comparing young children and older ones (Krieger et 
al, 2001; Wessels et al, 2003), as differences are great even for 1-year olds (0.08 g 
creatinine/day) relative to 5-year olds (0.4 g creatinine/day). 

Alternative approaches for adjusting for urine dilution are based on urinary specific gravity and 
on urinary output. Specific gravity adjustment accounts for all dissolved solids, with a specific 
gravity of 1.024 considered normal for adults. Both specific gravity and creatinine were 
measured in CTEPP urine samples. 

Urinary output among young children is often estimated with equations from the Exposure 
Factors Handbook. Zartarian et al (2000) estimated daily urinary output volumes of 500 and 800 
mL for the children 0-4 and 5-9 years of age, respectively, based on Geigy Scientific Tables. 
Estimated daily urinary output and creatinine excretion for children 3-12 years of age based on 
first morning void measurements and recorded ancillary information from the MNCPES are 
presented in Figure 8.8. 

• In unpooled samples from CTEPP, specific gravity of children’s urine averaged 1.020, 
significantly different than the 1.024 of adult urine (t-test, p < 0.001). 

• In the MNCPES study, the daily urine output rates (mean ± SD) increased from 13 ± 6 
mL/hr for 3-4 year olds to 19 ± 7 mL/hr for 11-12 year olds (Figure 8.8) based on first 
morning void samples with known volumes and void times. 

• In the MNCPES study, creatinine excretion rates (mean ± SD) increased from 10 ± 4 
mg/hr for 3-4 year olds up to 24 ± 12 mg/hr for 11-12 year olds (Figure 8.8). 

• There was neither a substantial nor consistent difference between sexes for either daily 
urine output or daily creatinine excretion rate, suggesting that sex is not an important 
predictor of creatinine excretion for pre-pubescent children (Figure 8.8). 

• Failure to appropriately account for creatinine excretion results in “over-correction” of 
children’s samples when making comparisons between CRE-adjusted adult and children 
urinary metabolite concentrations, making child levels appear higher by comparison. 

• An alternate approach for avoiding issues with variable urine volumes is to calculate 
biomarker excretion rates. This requires collection of complete voids, void volume 
measurements, and recording previous and final void times. 


144 


Overnight Urine Output (ml) 



□ Male 

□ Female 


Creatinine Concentration (mL) 



□ Male 

□ Female 


Overnight Urine Output Rate (mL/hr) 


Creatinine Excretion Rate (mg/hr) 


30 
25 
20 
15 
10 
5 
0 

3-4 5-6 7-8 9-10 11-12 



□ Male 

□ Female 


Age (years) 



□ Male 

□ Female 


Estimated 24-hr Urine Output (mL) 


Estimated 24-hr Creatinine Excretion (mg) 


600 

500 

j - 

r 400 

3 

CL 

O 300 


5 200 4- 


~ 100 4- 


ifl 


if 


3-4 5-6 7-8 9-10 

Age (years) 


□ Male 

□ Female 


11-12 



□ Male 

□ Female 


Figure 8.8 Estimates of age-specific urinary output and creatinine excretion, based on data from 
the MNCPES. 


145 












































































































































































































































































































































8.5 Relative Importance of Exposure Routes 

The relative importance of the dietary ingestion, indirect ingestion, dermal, and inhalation routes 
of exposure with respect to aggregate intake has been investigated with data from both the 
MNCPES and CTEPP studies. Daily inhalation and dietary intake estimates (ng/kg/day) for 
chlorpyrifos among children in MNCPES are available in Clayton et al. (2003). Estimated 
relative importance of the inhalation, dietary ingestion, and indirect ingestion routes of exposure 
to OPs and pyrethroids among children in CTEPP are presented in Morgan et al. (2004). 

• MNCPES chlorpyrifos data showed that ingestion was a more dominant route of intake 
than inhalation. Urinary metabolite levels, however, showed a stronger association with 
air (r=0.42, p<0.01) than with dietary (r=0.22, p<0.05) measurements. 

• Using MNCPES data as an input, the SHEDS model suggested (data not presented) that 
the dominant pathway for highly exposed chlorpyrifos users was non-dietary ingestion, 
followed by dietary ingestion. The model also suggested that the relative contribution of 
exposure pathways may differ by pesticide. 

• TCPy was found in several environmental media in CTEPP, particularly in solid food 
samples. Estimated intake of TCPy (Figure 8.9) was about 12 times higher than intake of 
chlorpyrifos for CTEPP children. Even when environmental TCPy is considered, nearly 
60% of the TCPy excreted in urine remained unaccounted for. This suggests that either a 
major pathway of children’s exposure to chlorpyrifos and TCPy remains unaccounted for 
in our algorithms or that some underlying assumptions are incorrect. 

• Despite indications that intake of TCPy from solid food may be responsible for the bulk 
of TCPy intake, intake from solid food and excretion are poorly correlated (r^O.Ol, 
Figure 8.10). The absorption rate for TCPy remains unknown, as does whether or not it 
is metabolized to other products in the body. 

• Based on exposure algorithms (with absorption assumed to be 50% by each route), the 
primary route of exposure and intake for chlorpyrifos and permethrin among CTEPP 
children was dietary ingestion (Table 8.8 and Figure 8.11). Inhalation was the secondary 
route for chlorpyrifos and diazinon (organophosphates); while indirect ingestion was the 
secondary route for permethrin (pyrethroid). 

• Based on algorithms, the contribution of diet to aggregate intake generally decreases as 
intake increases (Figure 8.12). Conversely, nondietary ingestion becomes increasingly 
important with increasing aggregate intake. 

• Unlike with TCPy, the estimated aggregate intake of cis- and frarcs-permethrin among 
CTEPP-OH children was close to the excreted amount of 3-PBA (Figure 8.12). 

However, children may have also been exposed to other pyrethroids that are metabolized 
into 3-PBA and could have contributed to the excreted amounts measured. 

• Our studies consistently report a low correlation between concentrations of urinary 
biomarkers of pesticide exposure and environmental concentrations. Algorithm-based 
estimates of aggregate intake do little to improve the correlation. A better understanding 
of how differences in activities between children affects intake may be needed. 

• Figures 8.14 and 8.15 present environmental and dietary levels of chlorpyrifos and 


146 


urinary concentrations of TCPy by study. There is little evidence that differences in 
environmental media concentrations translate into differences in urinary concentrations. 
The pattern is most similar between food and urine concentrations (Figure 8.15). 


Table 8.8 Estimated relative importance of the inhalation, dietary ingestion, and indirect 
ingestion routes of exposure among children in CTEPP NC and OH. 


Class 

Pollutants 

Apportionment of Aggregated Exposure/Dose 

OP Insecticide 

Chlorpyrifos and Diazinon 

NC: dietary ingestion ^inhalation > indirect ingestion 
OH: dietary ingestion > inhalation > indirect ingestion 

Pyrethroid Insecticide 

cis- and trans-Permethrin 

NC: dietary ingestion ^indirect ingestion > inhalation 
OH: dietary ingestion > indirect ingestion > inhalation 


120 
100 
80 

:§ 60 

©X) 

gf 40 
20 
0 

Figure 8.9 The median estimated intakes of chlorpyrifos and TCPy in CTEPP-NC compared with 
the excreted median amounts of TCPy in the preschool children s unne (Morgan et al ., 2005). 



Intake of Intake of Excreted amount 

chlorpyrifos TCP of TCP in urine 


147 





































Figure 8.10 Intake of environmental TCPy through the dietary route correlated poorly (^=0.01) 
with the amount of TCPy excreted in the urine of CTEPP-NC preschool children. 


CHLORPYRIFOS 


PERMETHRIN 


100 - 


o 

T> 

\ 

O' 

O' 

c 

Ld 

< 



0.01 - 


AGGR DIET INHAL INDIRECT DERMAL 



Figure 8.11 Estimated distributions of aggregate intake (“AGGR”) of chlorpyrifos and 
permethrin (ng/kg/day) and estimated distributions of the four contributing routes (diet, 
inhalation, indirect ingestion, and dermal) among CTEPP-OH children. 


148 
































































































Q) 

</> 

o 

Q 


c 

o 

•a 

3 

■O 


C 

o 

O 

3 

o 

H 


c 

0> 

o 

w 

0) 

0 . 


Dose (cis-Permethrin) 



□ inhal 

□ derm 

□ nondiet 

□ diet 


Lowest to Highest Aggregate Dose 


Figure 8.12 The contributions of inhalation, dermal absorption, diet, and nondietary ingestion to 
aggregate intake of c/s-permethrin. 


TCPy 

IOOOt 


>. 

(0 

"5> 


O) 

c 


100 ' 


10 - 


1- 



0.1 


Intake (NC) Excretion (NC) Intake (OH) Excretion (OH) 


3-PBA 



Figure 8.13 Children’s estimated aggregate intake of chlorpyrifos and permethrin compared to 
their measured urinary metabolites (CTEPP). 


149 





































































































































































CONCENTRATION (ng/g) CONCENTRATION (ng/g) CONCENTRATION (ng/m3) 


CHLORPYRIFOS 
INDOOR AIR (ng/m3) 


CHLORPYRIFOS 

OUTDOOR AIR (ng/m3) 


10000 - 



AZ MN NC FU NC DC OH IIU OH DC JAX OW CPPAC TEST 



10000-1 



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1000 7 


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n i i i i r 

UN NC HJ NC DC OH HU OHDC JAX 


CHLORPYRIFOS 
DUST CONCENTRATION (ng/g) 


CHLORPYRIFOS 
DUST LOADING (ng/cm2) 



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CHLORPYRIFOS 
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TCPY 

URINE (ng/ml) 



£ 

\ 

O' 

c 


< 
o: 

H 

Z 

U 

u 

z 

o 

o 



Figure 8.14 Distributions of TCPy in urine across studies (bottom right panel) in comparison to 
distributions of chlorpyrifos in indoor air, outdoor air, dust, and soil across studies. 


150 












































































































LOADING (ng/cm2) CONCENTRATION (ug/kg) LOADING (ng/cm2) 


CHLORPYRIFOS 

TOTAL SURFACE LOADING (ng/cm2) 


CHLORPYRIFOS 

TRANSFERABLE RESIDUE LOADING (ng/cm2) 


10000 

1000 

100 

10 

1 

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0.001 
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pur 


TEST 

pur 


TEST 

PRESS 


CHLORPYRIFOS 

SOLID FOOD CONCENTRATION (ug/kg) 


CHLORPYRIFOS 
SOLID FOOD INTAKE (ug/day) 



0.0001 - 

i i i r~ i i r 

AZ UN NC HU NC DC OH HJ OH OC Jtt 



CHLORPYRIFOS 
HAND LOADING (ng/cm2) 


TCPY 

URINE (ng/ml) 


1001 


10 


1 - 


o.i - 


0.01 1 


0.001 


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“1-1-1-1-1 n I 

MN NC MM NC DC OH HU OH DC CPPAE5 CPPAE5 

HR HW 


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Figure 8.15 Distributions of TCPy in urine across studies (bottom right panel) in comparison to 
distributions of chlorpynfos on surfaces, in solid food, and on hands across studies. 


151 



























































































































8.6 Model Predictions 


The Stochastic Human Exposure and Dose Simulation (SHEDS) model (Zartarian et al., 2000) 
provides route-specific estimates of aggregate exposures, relying on input data from assorted 
data sets, including those described in this report. The Safe Foods Project is currently 
developing an exposure-dose-response model to address cumulative risks associated with 
exposures to multiple pyrethroids. The Project intends to use the Exposure Related Dose 
Estimating Model (ERDEM) (Blancato et al ., 2004) to predict internal dose based on cumulative 
exposure estimates from SHEDS. The model will be used to identify critical pathways of human 
exposure and dose. A meaningful discussion of SHEDS and ERDEM is beyond the scope of this 
report, but an example of an important application of SHEDS is described below. 

• Use of the SHEDS model with MNCPES data (Figure 8.16) helped reveal the importance 
of accounting for exposures to the metabolite/degradate TCPy in environmental media. 
Without such accounting, the model under-predicted urinary TCPy concentrations. 

• SHEDS found that urinary biomarker concentrations depend mainly on dietary intake. 

An uncertainty analysis (independent of dietary) found other important factors to be: 
applied pesticide mass; surface area of treated rooms; time in treated rooms; air and 
residue decay rates; surface-to-skin transfer efficiency; dermal transfer coefficient; saliva 
removal efficiency; fraction hands mouthed; daily hand wash events; removal efficiency; 
maximum dermal loading; dermal absorption rate; and frequency of hand-mouth activity. 

• By identifying critical pathways of human exposure and dose (and their associated 
uncertainties), models such as SHEDS and ERDEM guide the planning for future 
measurement studies so that newly identified data gaps may be filled with real-world 
measurement data. 

• Applying SHEDS to different pesticide classes will provide information on degree to 
which factors that affect exposure differ across pesticide classes (e.g., pyrethroids vs. 
organophosphates). 



Modeled 


-Observed 


Figure 8.16 Comparison of TCPy in urine between SHEDS model and observed MNCPES data 
when TCPy in the environment is not considered (Source: Xue et al, 2004). 


152 









9.0 SUMMARY AND CONCLUSIONS 


In an effort to facilitate risk assessments that take into account unique childhood vulnerabilities 
to environmental toxicants, the National Exposure Research Laboratory (NERL) in the U.S. 
Environmental Protection Agency’s (U.S. EPA) Office of Research and Development (ORD) 
identified four priority research areas as representing critical data gaps in our understanding of 
environmental risks to children. These priority research areas are: 1) pesticide use patterns; 

2) spatial and temporal distributions of residues in residential dwellings; 3) dermal absorption 
and indirect (non-dietary) ingestion; and 4) dietary ingestion. Several targeted studies were 
conducted or financially supported by NERL to specifically address these priority research 
needs. The studies were designed to address the largest uncertainties associated with children’s 
exposure and aimed to produce sufficient real-world data to eliminate excessive reliance on 
default assumptions when assessing exposure. Significant progress has been made in each of the 
four priority areas leading to a more comprehensive understanding of the exposures resulting 
from children’s interactions with their environment. 

In the area of pesticide use patterns, our studies have taught us that pesticide products are likely 
to be found in nearly 9 out of every 10 homes. The most frequently applied of these products 
typically contain pyrethrins and pyrethroids (namely, permethrin, cypermethrin, and allethrin). 
The applications are more likely to be performed by an occupant than by a professional, with 
“crack-and-crevice” type applications favored over either the broadcast or total release aerosol 
types. The application frequencies appear to be higher in warmer climates, but no differences 
based on population density (urban vs. rural) or other socio-demographic factors including race, 
ethnicity, home type, income, and level of education are evident. Despite much effort in 
questionnaire development, we have had little success in correlating questionnaire responses 
with residue measurements. More effort is still needed to improve questionnaires and to ensure 
uniformity in inventory forms in future studies. Target populations for future studies should be 
chosen from areas that extend outside the limited geographic regions that have previously been 
studied to capture divergent use patterns, but previously studied populations should also be 
included to document trends. 

We have learned a great deal about spatial and temporal distributions of pesticide residues. 
Indoor air concentrations are typically ten-fold higher than outdoor concentrations, but 
surprisingly high outdoor air concentrations have also been measured. In the absence of any 
recent application, concentrations in indoor air are strongly influenced by vapor pressure. 
Immediately following an application, airborne concentrations peak within 24 hours and produce 
a concentration gradient with levels decreasing with distance from the application site. Southern 
states do have higher airborne concentrations than Northern states, but there is considerable 
overlap. Population density (urban vs. rural) and income level differences are evident. With 
surface residues, considerable variability exists not only among rooms but also in different 
locations within a room. Substantial translocation of pesticides from application surfaces to 
adjacent surfaces, and from outdoor surfaces to indoor surfaces has been observed. Cleaning 
activities and ventilation have been found to be important for both air and surface concentrations. 
Much, though not all, of what we have learned about spatial and temporal variability has come 
from organophosphate pesticides, and more studies with pyrethroids are needed. 


153 


These studies have added merit to earlier hypotheses that dermal transfer and indirect ingestion 
are important routes of children’s exposure to pesticides. In fact, the shift to less volatile, more 
organophilic pyrethroid pesticides magnifies the importance of particle-bound transfer and 
implies an increased significance of indirect ingestion. Substantial challenges still exist in this 
area. One challenge is to incorporate into estimates of dermal exposure what we have learned 
through laboratory studies of the importance of skin condition, contact motion, and number of 
contacts. Another challenge is to standardize the collection methods used to measure the surface 
residues that are a key part of dermal exposure estimates. A third challenge is to improve our 
indirect ingestion exposure algorithms to ensure that we are not missing major transfer 
mechanisms that may bridge the gap between what we are estimating as intake and what we are 
measuring as excreted. 

Analysis of the dietary ingestion components of our studies produce intake estimates that suggest 
dietary ingestion may often be the dominant route of exposure (even with pyrethroids despite the 
increased importance of the dermal and indirect ingestion routes). Low detection frequencies in 
food measurements, however, increase uncertainty, as does the questionable reliability of 
duplicate diet estimates for young children. Improvements are still essential in both the sample 
collection and the chemical analysis methods. Large differences in dietary exposure estimates 
among children in the same studies point to a need for a better understanding of the variability in 
dietary exposure. 

Clearly, more information is needed to assess the relative importance of the exposure routes 
under different conditions and with pesticides from diverse compound classes. More work is 
necessary to reconcile aggregate exposure estimates with levels of biomarkers measured in urine. 
Moreover, more work is needed to better understand how exposures and important exposure 
factors differ across age groups, as children move through different developmental stages. 

We anticipate that the analyses presented in this report will be useful to the EPA Program 
Offices, including the Office of Pesticide Programs and the Office of Children's Health 
Protection, in their risk assessment and management activities. Although much of this high- 
quality, real-world data has already been made available to the Program Offices piecemeal and 
by publication in the peer reviewed literature, we expect consideration of the data collectively to 
provide added value to the results of individual studies. Admittedly there are limitations inherent 
in the comparisons: studies were performed in different seasons, in different years, using 
different methods, and with different sample sizes. We are confident, however, that these 
analyses will facilitate more accurate exposure and risk assessments, thereby strengthening 
regulatory actions aimed at reducing risk, and helping to ensure that pesticides are appropriately 
regulated. 


154 


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159 


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160 


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161 


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Zartarian V, Ferguson A, and Leckie J. (1998) Quantified dermal activity data from a four-child pilot field study. J 
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Zartarian VG, Ozkaynak H, Burke JM, Zufall MJ, Rigas ML, Furtaw EJ Jr. (2000) A modeling framework for 
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nondietary ingestion. Environ Health Perspect 108(6):505-14. 


164 


APPENDIX A: Summary Statistics 















165 


















Table A.l Summary statistics for airborne chlorpyrifos concentrations (ng/m 3 ) by study. 


Max 

165 

NC 

135 

49.5 

0.91 

391 

45.9 

o 

oo 

On 

6.50 

84.9 

6.62 

On 

in 

5.5 

816 

1000 

95th 

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VO 

U 

Z 

ON 

vd 

r-H 

co 

d 

CO 

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d 

CN 

CN 

VO 

On 

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rd 

t> 

r-H 

CN 

CO 

On 

OO 

CN 

vq 

vd 


>n 

in 

VO 

oo 

o 

o 

o 

75th 

vq 

co 

u 

£ 

vq 

o 

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r-H 

d 

V 

m 

o’ 

N- 

vo 

d 

CN 

00 

vn 

On 

CO 

d 

■vt 

CN 

CO 

N" 

ON 

•vt 

rn 

CN 

vn 

CN 

r-H 

rn 

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c-~ 

50th 

e'¬ 

en 

cd 

u 

Z 

CN 

<q 

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o 

d 

V 

C" 

o 

vd 

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CN 

d 

vn 

o 

CN 

d 

N" 

d 

CN 

t~- 

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ON 

r-H 

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d 

o 

vn 

o 

ON 

CN 

25th 

CN 

cd 

V 

u 

z 

co 

ON 

d 

o 

vn 

d 

o 

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d 

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CN 

CN 

d 

CO 

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d 

r- 

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CO 

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V 

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cd 

CN 

vn 

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CN 

cd 

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d 

V 

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r-H 

d 

V 

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r-H 

d 

V 

rn 

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o 

d 

V 

o 

d 

V 

o 

d 

V 

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p 

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V 

VO 

d 

CO 

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V 

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n- 

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CN 

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rn 

vn 

t- 

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rn 

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on 

vn 

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z 

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vn 

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m 

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Indoor 

Outdoor 

Indoor 

Outdoor 

Indoor 

Outdoor 

Indoor 

Outdoor 

Indoor 

Outdoor 

Indoor 

Indoor 

Study 

NHEXAS-AZ 

MNCPES 

CTEPP-NC 

CTEPP-OH 

3 

CHAMACOS 

CPPAES (Day 1) 

Test House (Day 1) 


166 

































Table A.2 Summary statistics for airborne diazinon concentrations (ng/m 3 ) by study. 


o 

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i-i 

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d 

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o 

d 

o 

o 

d 

o 

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-d 

a 

s 

w 

s 

o 

a 

• r-H 

Max 

5.61 

6.85 

13.0 

1.95 

NC 

6.57 

7.8 

c~~ 

r-H 

95th 

5.61 

6.85 

4.82 

0.76 

NC 

6.57 

5.6 

t'~ 

r-H 

75th 

<3.0 

6.85 

2.11 

o 

o 

V 

NC 

<1.4 

vn 

o 

V 

2.6 

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cd 

V 

o 

rd 

V 

OO 

o 

r-H 

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V 

NC 

<1.4 

vn 

o 

V 

<n 

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V 

25th 

<3.0 

<3.0 

o 

o 

V 

o 

© 

V 

NC 

<1.4 

vn 

o 

V 

vn 

O 

V 

Min 

<3.0 

o 

cd 

V 

o 

r—H 

O 

V 

o 

r-H 

o 

V 

NC 

<1.4 

<0.5 

vn 

o 

V 

GSD 

NC 

NC 

CO 

NC 

NC 

<1.4 

NC 

NC 

GM 

NC 

NC 

0.59 

NC 

NC 

NC 

NC 

NC 

as 

NC 

NC 

1.87 

NC 

NC 

NC 

NC 

NC 

Mean 

NC 

NC 

1.53 

NC 

NC 

NC 

NC 

NC 

%Det 

Tf 

r-H 

CO 

CO 

r- 

VO 

(N 

»—H 

o 

r-H 

vn 

r-H 

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£ 

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Outdoor 

Indoor 

Outdoor 

Indoor 

Outdoor 

Indoor 

Outdoor 

c3 

i 

GO 

CO 

< 

<u 

r-H 

•s 

H 

Study 

NHEXAS-AZ 

MNCPES 

XVf 

CHAMACOS 


167 


NC, not calculated due to low detection frequency 


























































Table A.4 Summary statistics for airborne c/s-permethrin concentrations (ng/m 3 ) by study. 


Max 

15.7 

20.9 

0.23 

34.4 

1.62 

6.50 

OO 

t"; 

92.5 

2.29 

rn 

r-H 

3 

T-H 

NC, not calculated due to low detection frequency 

Table A. 5 Summary statistics for airborne trans- permethrin concentrations (ng/m 3 ) by study. 

Max 

13.9 

q 

OO 

t-H 

8.12 

40.9 

1.01 

6.84 

1.32 

■'T 

m 

10.2 

1.8 

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d 

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m 

vd 

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in 

vo 

d 

V 

vo 

d 

V 

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CN 

d 

On 

O 

O 

3- 

o 

d 

V 

^H 

Tf 

d 

o 

t-H 

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V 

o 

3; 

d 

V 

o 

3^ 

d 

V 

o 

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m 

CN 

VO 

d 

V 

vo 

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O 

d 

V 

ON 

o 

d 

V 

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o 

d 

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CN 

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d 

V 

o 

d 

V 

o 

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d 

V 

VO 

q 

C3 

o 

in 

CN 

vo 

d 

V 

VO 

d 

V 

25th 

OV 

o 

d 

ON 

O 

O 

V 

3- 

o 

d 

V 

o 

d 

V 

o 

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d 

V 

o 

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d 

V 

o 

d 

V 

q 

V 

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d 

V 

vo 

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V 

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CN 

ON 

o 

d 

V 

ON 

o 

d 

V 

On 

O 

d 

V 

o 

d 

V 

o 

d 

V 

o 

N" 

d 

V 

o 

d 

V 

q 

V 

OO 

q 

CN 

vo 

d 

V 

VO 

d 

V 

Min 

ON 

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d 

V 

ON 

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d 

V 

h - 

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d 

V 

o 

d 

V 

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d 

V 

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3* 

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3- 

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V 

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vo 

d 

V 

vo 

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o 

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d 

V 

vo 

d 

V 

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rn 

U 

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O 

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O 

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00 

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U 

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O 

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Q 

OO 

O 

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in 

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z 

u 

z 

cn 

«n 

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z 

O 

z 

u 

z 

m 

uS 

CN 

o 

Z 

O 

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GM 

m 

CN 

O 

T-H 

t—H 

d 

o 

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O') 

d 

o 

z 

u 

z 

u 

z 

u 

z 

3 

cn 

T-H 

u 

z 

o 

z 

s 

o 

t-H 

d 

o 

z 

o 

Z 

«n 

cn 

d 

u 

z 

u 

z 

u 

Z 

On 

t 3‘ 

cn 

m 

CN 

o 

z 

o 

Z 

as 

t—H 

CN 

CN 

3- 

cn 

CN 

u 

z 

m 

OO 

Tt 

u 

£ 

o 

z 

u 

z 

o 

z 

O 

OO 

d 

u 

z 

o 

z 

Q 

OO 

m 

ON 

T-H 

u 

z 

o 

z 

ON 

OO 

3 

o 

z 

u 

z 

u 

z 

q 

cn 

"3- 

o 

CO 

u 

z 

o 

z 

Mean 

OO 

r- 

d 

o 

IT) 

o 

u 

z 

ON 

t—H 

o 

z 

o 

z 

o 

z 

o 

£ 

in 

in 

u 

z 

O 

£ 

n 

<D 

s 

H-H 

VO 

d 

o 

z 

u 

z 

CN 

q 

T-H 

u 

z 

o 

z 

u 

z 

CO 

m 

ci 

u 

z 

o 

z 

%Det 

VO 

00 

On 

VO 

m 

in 

VO 

On 

t-H 

CN 

CN 

(N 

3 

3 

VO 

m 

o 

3 

CN 

m 

Q 

£ 

CO 

vo 

CN 

3 

3 

t—H 

m 

VO 

On 

t-H 

On 

r" 

t—H 

VO 

OO 

r- 

vo 

o 

Z 

h - 

VO 

On 

00 

t—h 

m 

OO 

3 - 

o 

•'3' 

t"- 

3- 

r-H 

cn 

3 

t—H 

On 

On 

O 

CN 

o 

CN 

Z 

OO 

VO 

VO 

On 

<n 

OO 

I}- 

o 

N" 

^3" 

cn 

r-H 

ON 

ON 

On 

OO 

Location 

Personal 

Indoor 

Outdoor 

Indoor 

Outdoor 

Indoor 

Outdoor 

Indoor 

Outdoor 

Indoor 

Outdoor 

Location 

Personal 

Indoor 

Outdoor 

Indoor 

Outdoor 

Indoor 

Outdoor 

Indoor 

Outdoor 

Indoor 

Outdoor | 

Study 

MNCPES 

CTEPP-NC 

CTEPP-OH 

3 

>—> 

CHAMACOS 

>N 

33 

2 

OO 

MNCPES 

CTEPP-NC 

CTEPP-OH 

3 

CHAMACOS 


168 


NC, not calculated due to low detection frequency 

























































Table A.6 Summary statistics for airborne TCPy concentrations (ng/m 3 ) by study. 


Max 

1040 

9.06 

42.0 

4.86 

95th 

14.3 

1.57 

8.60 

0.88 

75th 

3.99 

0.40 

1.74 

0.36 

50th 

1.77 

0.22 

0.65 

0.21 

25th 

oo 

o 

0.13 

0.43 

0.13 

Min 

<0.09 

<0.09 

0.09 

<0.09 

GSD 

OO 

rn 

2.6 

rn 

CN 

CN 

GM 

oo 

0.24 

tt 

oo 

o 

0.22 

as 

12.47 

0.9ll 

4.62 

oo 

o 

Mean 

4.68 

0.44 

1.97 

0.32 

%Det 

66 

oo 

oo 

100 

oo 

oo 

£ 

148 

140 


m 

m 

r—H 

Location 

Indoor 

Outdoor 

Indoor 

Outdoor 

Study 

CTEPP-NC 

CTEPP-OH 



co 

a 
o 
*-* 
cS 


C 


<U 

o 


CS 

O 

o 


Ph 

>—H 




Max 

27.4 

49.6 

95th 

5.68 

2.44 

75th 

o 

0.77 

50th 

0.53 

0.33 

25th 

0.35 

0.14 

Min 

<0.09 

<0.09 

GSD 

3.1 

3.7 

GM 

0.64 

0.36 

as 

3.62 

5.93 

Mean 

1.52 

oo 

rr 

%Det 

On 

'■O 

oo 


147 

rH 

Location 

Indoor 

Outdoor 

Study 

CTEPP-OH 


169 





































Table A. 8 Summary statistics for chlorpyrifos concentrations measured in soil (ng/g). 


* 

OS 

o 

SO 

o 

SO 

o 

cd 

.* 

r- 

r- 

cO 

»—< 

m 

£ 

CN 

1—4 

o' 

Os 

CN 

so" 



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IN 

SO 

OO 

SO 

oo 

CD 


sd 

in 

ro 


so 

Os 

V 


o 

r-H 

SO 

CN 

.5 

o 

m 

in 

CN 

CN 

m 


1—4 

V 

o 

o 

Os 

CO 

V 

n 

V 

V 

ro 



•p 

o 

m 

IT) 

in 

>n 

<n 

4-3 

O 

r—H 

V 

o' 

o' 

o 

o 

V 

<n 

V 

V 

V 

V 


-S 

o 

«n 

in 

m 

in 

m 


i—4 

o 

o 

cd 

o 

V 

CN 

V 

V 

V 

V 

V 


s 

O 

ST) 

«n 

>n 

n 

>n 

§ 

V 

o 

o 

O 

o 

V 

V 

P 

u 

U 

U 

U 

O 

o 

00 

O 

z 

£ 

z 

Z 

z 

z 

s 

u 

o 

u 

o 

u 

u 

o 

z 

z 

z 

z 

z 

z 

P 

u 

u 

o 

u 

u 

u 

C/5 

z 

z 

z 

z 

z 

z 

s 

u 

u 

u 

u 

u 

u 

CO 

<L> 

£ 

z 

z 

z 

z 

z 

z 

%Det 

ro 

Os 

00 

Os 

oo 

m 




ro 

CO 

CN 

c 

CN 

oo 

CO 

r- 

so 

n 


O 

CN 

r-H 

CN 

1-H 












<u 


<u 

<D 

a, 

<u 

O 

h 

U 

la 

Vh 


£ 

c 

Cd 

d 

cd 

cd 


c 

c 

o 

c 

o 

o 

Vh 

o 

o 


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53 

53 

cd 

P 

53 

cd 

P 

cd 

P 

T3 







O 

f— « 

r-H 


1—< 


•—4 

3 

d 

d 


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d 

0 

£ 

C/5 

C/5 


C/5 


C/5 









C/D 

U 


53 



£ 

w 

Ph 

£ 


O 

v—✓ 


u 

a 

C/5 

U 

Oh 

Oh 

W 


Ph 

Ph 

W 


o 

u 

* 


H 


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u 


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o 

ea 

3 

3 

o 

H-> 

o 

z 

#S 

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Z 




si 

O 

S> 


c n 
<3 

<D 


P 

05 

C/5 

<D 


PH 



00 

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C/5 


cd 

4-> 

C/5 



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l 

H 


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so 

CN 


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CN 


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ro 

r—4 


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CN 

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£ 

CN 

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r-H 

cd 


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Os 

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Os 

1—4 

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CN 











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m 

Os 

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3- 

m 

ro 

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CN 

r-H 

OS 

oo 

CN 

O 


cd 

cd 

p 

cd 



OS 

3" 

r-H 

oo 

CN 

rP 

SO 

SO 

oo 

CN 

Os 

oo 


f-H 

3- 

Os 

O 

CN 

<n 

in 

oo 

in 

r-H 

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y—* 

o 


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p 


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3" 

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CN 

m 

I 

CN 

in 

o 

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y—4 




cd 


cd 

o 

cd 

cd 









o 











p 

CN 

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CN 

OO 

3" 


m 

CN 


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»n 

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ro 

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o 

o 

p 

O 

o 


IN 

3" 

3" 

Os 

ro 

CN 

N 

SO 

od 

t 


cd 


cd 

cd 

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cd 









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q 

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Os 

r—4 

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£ 

o 

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p 

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cd 

O 

o 

cd 



CN 

vq 

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C> 

3- 

V 


V 

o 

o 

cd 


V 







P 

ro 

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3" 

Os 

oo 

CN 


IN 

<n 

r-H 

r> 

N 

C/5 

CN 


SO 

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3- 


cn 

ro 

<n 

CN 

3- 

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£ 

CN 

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3- 

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N 

CN 

3" 

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f—4 


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3- 

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ro 

ro 


so 

(N 

o 

o 


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r- 




cd 

o 

cd 

cd 

cd 

o 







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o 

ro 

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3" 

ro 

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3" 

oo 

so 

ro 

m 

ro 

ro 


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in 

m 

oo 

oo 

cd 

cd 

o 

cd 

cd 

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cd 


3- 

r—4 

CN 

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CN 

SO 

g 

3^ 

3" 


SO 

Os 

3" 


m 

N- 

r-H 

CN 

O 

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£ 

ro 

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(N 

o 

t-H 

i-H 


r-H 

ro 

r-~ 

t 

r- 

cd 

cd 

cd 

r “ H 

cd 

p 


3- 

CN 

oo 

CN 

ro 




cd 


cd 







%Det 

r- 

o 

o 

o 

o 

m 


o 

o 

o 

O 

>n 

n- 

o 

o 

o 

o 

Os 


o 

o 

o 

o 

Os 




»—* 









q 

cn 


Os 

o 

ro 

o 


^■H 

Os 

o 

m 

o 


»—H 

CN 

T—4 

CN 

CN 

CN 


CN 

r-H 

CN 

CN 

CN 















CN 













1—< 












a. 

VI 


O 


<U 




o 


§ 


<D 


<U 

la 



O 

t-H 

<u 


3 


5 

cd 

3 

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d 

cd 

d 

cd 

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2 

<D 

2 

c 

o 

G 

O 



G 

O 

o 

>> 

G 

o 


a 

X 

cd 

Q 

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cd 

Q 



53 

cd 

Q 

X 

cd 

p 



o 












-a 

B 

4-» 

iyD 

d 


4-* 

C/) 

d 


4-* 

C/3 

G 


4—» 

C/D 


00 

2 


4H 

C/3 

G 

o 

’S 

3 

Q 


p 


Q 


Q 


Q 


p 

o 

cd 

> 

Wh 


U-. 


o 


»H 


Wh 


(D 

<D 

£ 

o 

£ 


o 

jp 


C/3 

3 

O 


O 


o 


C/3 

3 

O 


Ph 


Ph 


53 


Ph 


Uh 


53 


(S’ 

/ _^ 




C/5 






C/5 


< 

u 


53 


O 


u 


53 


o 

*G 

a 

1 

c/3 

< 

Ph 


O 

Ph 


o 

< 


£ 

Ph 


O 

Ph 


u 

< 

X 

Ph 


Ph 




Ph 


Ph 



C/D 

w 

W 


w 




w 


w 




pT| 

H 


H 


53 


H 


H 


53 


2 

u 


U 


U 


U 


U 


U 



( z rao/gu) 




(§/§u) 




SrnpBoq 



U0IJEJJU9DU03 


170 




















































Table A. 10 Summary statistics for diazinon concentrations measured in soil (ng/g). 


Max 

24.9 

5470 

<0.5 

28500 

LO'L 

o 

o 

o 

o 

l“H 

r—H 

2490 

95th 

o 

T-H 

V 

''t 

CN 

N- 

l/D 

d 

V 

CN 

C-; 

Tj- 

r- 

o 

t< 

On 

(N 

24900 

75th 

o 

V 

<n 

d 

V 

to 

d 

V 

On 

On 

O 

m 

d 

V 

CN 

V 

21100 

50th 

o 

V 

>n 

d 

V 

<0.5 

«o 

d 

V 

>n 

d 

V 

CN 

V 

16200 

25th 

o 

v* 

V) 

d 

V 

m 

O 

V 

in 

d 

V 

<n 

d 

V 

CN 

V 

12600 

Min 

o 

"v 

«n 

o 

V 

«n 

o 

«n 

O 

V 

<n 

o 

CN 

V 

10100 

GSD 

o 

£ 

O 

55 

U 

£ 

u 

£ 

U 

£ 

V 

£ 

I/O 

h; 

r-H 

GM 

o 

£ 

U 

O 

£ 

u 

£ 

O 

£ 

u 

£ 

00091 

SD 

o 

z 

u 

£ 

u 

£ 

u 

z 

o 

£ 

u 

z 

6140 

Mean 

u 

£ 

o 

£ 

o 

z 

u 

£ 

u 

z 

o 

z 

16900 

%Det 

n- 

oo 

o 

■^r 

CO 

ON 

o 

(N 

o 

o 

y—i 

« 

(N 

o 

On 

CN 

m 

r- 

CN 

NO 

r-H 

r- 


Group 

Home 

Home 

Daycare 

Home 

Daycare 

Daycare 

Home 

Method 

o 

C/D 

’o 
c n 

• ^ 
o 

C/D 

‘o 

C/D 

O 

C/D 

Study 

MNCPES 

CTEPP (NC) 

CTEPP (OH) 

CCC 

H 

W 


'w) 

'Sh 

c 

o 

* l-H 

cs 

H 

-*-> 

C 

<u 

o 

a 

o 

o 

r o 

n 

| 

c. 

Max 

oo 

o 

5.63 

9.86 

6.24 

1.25 

r-H 

oo 

O 

d 

oo 

NO 


11000 

o 

oo 

00 

vo 

79900 

1630 

2550 

o 

o 

o 

ON 

3- 

i-H 

95th 

0.18 

0.123 

9.86 

0.31 

0.39 

oo 

Tf- 

o 

d 

OO 

VO 


388 

6880 

1710 

1610 

1470 

149000 

75th 

0.035 

NO 

O 

o 

d 

0.154 

o 

d 

0.06 

0.0032 

N; 

»—H 


54.4 

oo 

CO 

r-H 

73.2 

210 

74.4 

18500 

50th 

0.002 

0.0016 

r- 

r- 

o 

d 

CN 

o 

o 

d 

0.022 

0.0021 

0.35 


17.5 

65.2 

19.8 

o 

d 

3 - 

58.8 

312 

25th 

CN 

O 

p 

d 

V 

0.0006 

0.0032 

o 

o 

d 

N- 

O 

O 

d 

o 

o 

p 

d 

0.092 


7.90 

26.0 

9.72 

28.4 

21.3 

654 

Min 

CN 

O 

o 

o 

V 

<0.0003 

0.0002 

<0.0003 

o 

o 

o 

■Cf 

O 

o 

o 

d 

>n 

o 

o 

o 


CN 

V 

3.06 

CN 

V 

5.08 

7.75 

256 

00 

C 

• rH 

'O 

aj 

JO 

4=1 

4—» 

O 

42 

C/D 

c3 

"O 

<D 

-*-> 

C 

CD 

CO 

<D 

J-H 

a, 

r\ 

4—» 

CO 

3 

C 

• H 

T3 

<D 

H 

3 

CO 

a 

<D 

s 

3 

O 

3 

•fH 

s 

’S 

Vh 

£ 

CO 

a 

• H 

4-* 

CO 

• rH 

4— » 

cd 

4-* 

CO 

>N 

t-j 

3 

i 

00 

GSD 

r-H 

t< 

oo 

oo 


m 

t< 

On 

in 

CN 

cn 

CN 


in 

NO 

•n 

7.2 

oo 

O) 

cn 

2.1 

GM 

t-~ 

o 

o 

d 

0.0025 

0.0235 

N- 

O 

O 

d 

0.02 

0.0022 

0.44 


YVZ 

58.6 

34.3 

e'¬ 

en 

r- 

53.9 

4990 

as 

0.062 

0.638 

2.25 

0.59 

0.27 

oo 

r-H 

o 

d 

16.5 


1380 

1560 

8470 

472 

562 

53000 

Mean 

0.035 

0.0964 

0.571 

0.094 

d 

0.0065 

5.72 


282 

439 

1360 

260 

202 

29200 

%Det 

rt 

NT) 

VO 

On 

100 

NO 

ON 

100 

100 

o 

o 

^H 


VO 

ON 

100 

VO 

On 

001 

100 

100 

c 

cn 

f-H 

CN 

1—H 

ON 

r-H 

9120 

CO 

CN 

o 

CN 

r- 


*—H 

CN 

On 

O 

CN 

r—H 

cn 

CN 

o 

CN 

r- 

r-H 

Group 

Children <12 

Home 

Daycare 

Home 

Daycare 

5 

All 


Home 

Daycare 

Home 

Daycare 

All 

All 

Method 

Vacuum 

Floor Dust 

Floor Dust 

House Dust 

Floor Dust 


Floor Dust 

Floor Dust 

House Dust 

Floor Dust 

Study 

NHEXAS-AZ 

CTEPP (NC) 

CTEPP (OH) 

CHAMACOS 

PET 


CTEPP (NC) 

CTEPP (OH) 

CHAMACOS 

PET 

< 

CD 

f-H 

•3 

H 


( z mo/8u) 

SrnpnoT 


m 

U0IJBJJU9DU03 


171 


NC, Not calculated 


























































Table A. 12 Summary statistics for c/s-permethrin concentrations measured in soil (ng/g). 


X 

on 

o 

NO 

o 

VO 

o 

d 

s 

H-’ 

CN 

N- 

r-H 

o 

co 

On 

CN 

o’ 

V 

VO 


O 

C" 

NO 

OO 

VO 

oo 

in 

V 

no 

N- 

cd 

o 

NO 

Ov 

r-H 

o 

r-H 

V 

CN 

•O 

O 

00 

VO 

VO 

VO 

VO 

to 


o 

o 

o 

o 

V 

r- 

V 

V 

V 

V 

V 


•3 

o 

<10 

vo 

o 

VO 

o 

VO 

o 

VO 

o 

VO 

V 

vo 

V 

V 

V 

V 


-g 

o 

VO 

VO 

VO 

vo 

vo 

4-3 

V 

o 

o 

o 

o 

V 

CN 

V 

V 

V 

V 


Min 

o 

VO 

VO 

VO 

VO 

vo 

t—H 

V 

o 

V 

cd 

V 

o 

V 

O 

V 

Q 

U 

O 

O 

U 

O 

u 

C/5 

O 

2 

2 

2 

z 

2 

Z 

s 

o 

u 

U 

u 

U 

u 

o 

2 

2 

z 

z 

2 

2 

Q 

u 

u 

u 

u 

u 

u 

c/5 

2 

2 

z 

z 

2 

2 

Q 

o 

u 

u 

u 

u 

u 

<u 

2 

2 

z 

z 

2 

2 

s 







3 

Q 

CO 

On 

oo 

ON 

o 

co 


t—H 


co 


CN 








a 

CN 

oo 

co 

t> 

NO 



O 

CN 

r-H 

CN 

r-H 

t-H 



t—H 








CD 


<D 

<d 

&, 

<D 

<D 

V-. 

CD 

H 

h 

3 

S 

a 

d 

O 

a 

d 

o 

d 

o 

l_4 

o 

o 

jo 

o 

>N 

Jo 

o 

X 

X 

d 

Q 

X 

d 

Q 

Cd 

Q 

T3 







O 

r—4 

r-H 


T-H 


r-H 

3 

O 

o 


d 


d 

<d 

S 

00 

00 


00 


oo 









QQ 

U 


X 



T3 

w 

Oh 

& 


O 


U 

3 

C/5 

o 

Oh 

Oh 

W 


Oh 

Oh 

W 


O 

u 



H 


H 





u 


U 




*o 

0) 

■*-* 

”3 

”3 

o 

H-» 

o 

2 

r\ 

u 

2 



X 

o 

co 


m 

On 


o 

o 

o 

o 

o 

d 




o 

CN 


o 

o 

o 

CO 

i-~ 

s 

CN 

OO 


vd 

cd 


o 

o 

On 

NO 

On 

NO 

N - 

o 

On 








t-H 

CN 

r~ 










ro 





-S 

■ 3 - 

ON 

vo 

CN 

r- 


o 

O 

o 

O 

O 

vo 

ON 

On 

no' 

•of 

oo 

oo 

t-H 


o 

o 

co 

co 

t-H 


rn 

3 

cd 


r-H 

IN 

On 

NO 

IN 

OO 

CO 

oo 

vo 








CN 

r-H 




-S 

_ 

OO 

vo 

00 



O 

o 

O 

o 

oo 

vo 

o 

t-H 

t> 

CN 

NO 

cn 


vo 


VO 

vo 

On 

^r 

o 

1 

<d 

cd 

o 

cd 


oo 

CN 

CN 

vo 

oo 

r—H 

vo 


m 


vo 

r- 

vo 


N- 

NO 

o 

o 

vo 


o 

ON 


CN 

t-H 


O 

o 

c 

T-H 

N" 


r-; 

NO 

o 

cd 

o 


oo 

OO 

b" 

O 

CO 


o 

O 

cd 


cd 







-g 

NO 


vo 


r- 


r~ 

VO 

r- 

OO 

CO 

vo 

CN 

CN 

OO 

f-H 

o 

vo 


N- 

vo 

ON 

r-H 

r-H 

O 

r-H 

o 

o 

o 


m 

•^r 

t-H 

of 



O 

o 

<d 














cd 







g 

CN 

vo 

CN 

r-H 

m 


t-H 

m 

no 

N- 

NO 

• rH 

s 

O 

o 

o 

o 

<d 

o 

o 

o 

o 

o 

r-H 

o 

o 


in 

NO 

r-H 

no' 

CN 

vd 

CN 


cd 




cd 







Q 

oo 

m 

vo 

o 

N" 


NO 

CO 

CO 

NO 

CN 

00 

oo 

oo 

t< 

vd 

cd 



■nj - " 

■'cT 

CN 

Tf 

O 












s 


r- 

C<0 

NO 

m 


vo 

o 

CN 

oo 

N- 

o 

o 

NO 

CN 

r-H 


ON 

N" 

IN 

NO 

r-H 

o 

o 

vo 

cd 

o 

o 

cd 

o 

cd 


On 

T-H 

VO 

ON 

co 

SD 

CN 

NO 

CN 

NO 

CO 


O 

O 

o 

O 

o 

O 

ON 

m 

C<0 

NO 


O 

NO 

vo 

o 

T-H 

ed 

3 

r-H 

o 

cd 


ON 

CN 

N 

NO 

o 

oo 

CO 

O 

CN 

g 

vo 


m 

oo 

o 


o 

o 

o 

o 

CO 

d 

<D 

s 

C" 


oo 

IN 

m 


oo 

o 

CN 

NO 

CN 

On 

cd 

vd 

cd 

cd 

o 

cd 


o 

NO 

vo 

CO 

CO 

<N 

N- 

T—H 

On 

o 

Q 

O 

o 

o 

o 

o 


o 

o 

o 

o 

O 

O 

o 

o 

o 

o 


o 

o 

o 

o 

O 

»—( 

r—1 

f—( 

r—1 

r— < 


r-H 

i—4 

T—H 

1 1 

r—H 

NO 

0 s - 












o 


o 

o 

CO 

O 


T-H 

o 

O 

CO 

O 


CN 

CN 

CN 

CN 

CN 


CN 

CN 

CN 

CN 

CN 


t-H 


1 < 




r-H 


r-H 





<D 


<u 




<D 


CD 


Oh 

<D 

u. 

O 




<u 


<D 

c3 


o 

o 

Wh 

s 

o 

CO 

o 

>N 

a 

o 

CCJ 

o 

Jo 

IIV 


a 

o 

cd 

o 

>N 

a 

o 

IIV 

o 

ffi 

d 

Q 

X 

d 

Q 



X 

d 

Q 

K 

d 

Q 


•O 

4-* 

(/) 

d 


4H 

CO 

d 


■M 

(2) 

d 


4-» 

C/D 

d 


4~» 

C/D 

d 


4H 

C/D 

d 

O 

Si 

Q 


Q 


Q 


Q 


Q 


Q 

H 

Vh 


Ih 


<u 


Vh 


Vh 


CD 

<D 

S 

o 

_o 


o 

J2 


V5 

3 

O 


o 


o 


C/2 

3 

O 


Hh 


Uh 


X 


Uh 


Uh 


X 


/ _ _ 


K 


C/5 






C/5 


U 



o 


O 


X 


o 


& 


o 


u 

<r 


& 


o 


u 

< 

3 

0h 


Oh 




0h 


Dh 



Oh 


Oh 




Oh 


Plh 



(/) 

W 


w 


<J 


w 


w 




H 


H 


K 


H 


H 


X 


O 


U 


U 


U 


o 


u 



( z mo/3u) 




(S/Su) 




SuxpBoq 



uoumjnaouo^ 


172 


















































Table A. 14 Summary statistics for Jraws-permethrin concentrations measured in soil (ng/g). 


* 

o 

o 

o 

<n 

no 

cd 

r-H 

CN 

o 


co 

s 

N© 

CN 

N" 

T— H 

V 


*3 

On 

O 

V© 

»n 

o 

in 


CN 

o 

d 

CN 

On 

r—H 

CN 

ni 

V 

r-H 

■5 

»n 

in 

«n 

in 

>n 

V 

'O 

d 

d 

d 

d 

r- 

V 

V 

V 

V 


■5 

in 

>n 

in 

«n 

m 

V 

o 

d 

d 

d 

d 

m 

V 

V 

V 

V 


& 

m 

>n 

<n 

m 

«n 

>n 

d 

d 

d 

d 

V 

CN 

V 

V 

V 

V 


Min 

m 

d 

*n 

d 

in 

d 

<n 

d 

m 

V 

V 

V 

V 

V 


Q 

O 

u 

V 

U 

u 

C/5 

O 

£ 

£ 

z 

£ 

z 

s 

o 

u 

u 

o 

u 

o 

z 

z 

£ 

z 

£ 

Q 

o 

u 

u 

u 

o 

c/5 

£ 

z 

z 

z 

z 

s 

u 

o 

u 

u 

u 

Cd 

<D 

z 

£ 

z 

£ 

£ 

s 






%Det 

CN 

oo 

l© 

o 

l© 

CN 





g 

On 

co 

H- 

N" 

r- 


CN 

r—H 

CN 

r-H 

y—< 






r —h 



© 


© 

© 

Cl, 

3 

© 

s 

£ 

O 

© 

6 

Wh 

cd 

o 

cd 

o 


o 


o 

>, 


o 

X 

«3 

Q 

a 

cd 

Q 

cd 

Q 

T3 






O 

,_f 





■5 

• H 

o 


• r-4 

O 


• rH 

o 

© 

C/5 


c/5 


C/5 

s 












U 


X 




£ 


o 


u 

3 

Oh 


&H 


u 

Ph 


P-, 


u 

C/5 

w 


W 



H 


H 




U 


U 




© 
*—» 
ec 


3 

*3 

o 


c. 

U 

£ 



* 

no 

CN 

o 

r-~ 

oo 


o 

o 

o 

o 

o 

cd 

CN 

CN 


ud 

H- 

r—H 

<n 


o 

o 

o 

in 

o 

S 

On 

«n 

d 


o 

CN 

On 

On 

oo 

oo 

ON 

m 

CN 

OO 








CN 

CN 

r- 


»-H 








CO 





3 

CN 

OO 

N© 

CN 

oo 


o 

O 

o 

o 

O 

m 

On 

N" 

oo 

H- 

OO 


CO 


o 

O 

r-H 

CN 

o 

d 

ro 

H- 

d 


Tf 

On 

Os 

o 

CN 

On 

m 

co 

r-H 









CN 



r — < 

£ 

oo 

oo 


r- 

NO 


O 

o 

O 

o 

O 

m 

r~~ 

CO 

co 

*—< 

«n 

o 


m 

ro 

t" 

NO 

in 

d 


d 

d 

d 


oo 

r—< 

oo 

r—4 

CN 

r-H 

oo 

CN 

r—4 

-c 

On 


m 

NO 

CN 


ON 

NO 

H- 

H" 

oo 


O 

N- 

o 

CN 

o 


CN 

'© 

H- 

m 

o 

to 

d 

d 

d 

d 

d 


NO 

oo 

m 

in 

NO 

.5 

m 


o 

C" 

H- 


t" 

CN 

CN 

CN 

O 

>n 

CN 

r-H 

co 

r—H 

H- 

r—H 


NO 

n- 

m 

NO 

r-H 

O 


o 

O 

O 


CN 

m 

»-H 

co 

m 


d 

d 

d 

d 

d 







Min 

N© 

V/O 

CN 

r~- 

CN 


m 


m 

NO 

CN 

o 

o 

o 

o 

O 

O 

o 

p 

O 

O 


»—i 

tn 

CN 

r-H 

NO 

r—H 

CN 

CO 



o 

o 

d 

d 








d 











Q 

o 

CN 

CN 

o 



o 

in 

O 

r- 

o 

00 

r-H 

od 

oo 

v© 

rn 


in 

N- 

>n 

CN 

H" 

O 












S 

ON 

On 

>n 

o 

ro 


m 

o 

cn 

H" 

«n 

o 


o 

CN 

o 


m 

r-H 

in 

oo 

in 

o 

d 

d 

d 

d 

d 


oo 

— 

H- 

r- 

NO 

Q 

On 

CN 

NO 

o 

CO 


o 

o 

o 

o 

o 

00 

On 

_• 

CN 


*—< 


o 

CN 

CN 

CN 

CO 

CN 

o 

<N 

N- 


d 


H" 

o 

r~- 

CO 

OO 

CN 

o 

N- 








co 





3 


ON 

NO 

m 

NO 


o 

o 

o 

O 

o 

cd 

On 

<n 

r" 

o- 

o 


CN 

o 

N- 

NO 

NO 

© 

s 

d 

<n 

d 

d 

d 


r—4 

NO 

VO 

m 

co 

CN 

CN 

1 1 

OO 

-4—» 

O 

o 

o 

o 

o 


o 

o 

O 

o 

o 


O 

o 

o 

o 

o 


o 

o 

o 

o 

o 

Q 



T— H 

i—H 

1—4 


*—H 

r-H 

^H 

r-H 

r-H 

vP 

0 s * 












G 

_ 

o 

oo 

CN 

O 


4—H 

o 

OO 

CN 

O 


CN 

CN 

r-H 

CN 

CN 


CN 

CN 

r-H 

CN 

CN 


> "4 






1 < 


r—4 





<D 

c3 


V 




© 


© 


Q. 

s 

© 

C 

u. 

cd 



© 

P 

cd 

© 

G 

Ih 

cd 

, 

O 

G 

o 

© 

>, 

G 

O 

© 

Jo 



G 

O 

o 

>% 

G 

O 

o 

>5 


O 

a 

cd 

Q 

a 

cd 

Q 



a 

cd 

Q 

a 

cd 

Q 


-o 

o 

C/5 

3 

Q 


•4—» 

C/5 

3 

Q 


4-» 

CO 

Q 


4-* 

CO 

G 

Q 


4-i 

CO 

G 

Q 


4-» 

co 

G 

Q 




1-4 


© 


u 


Vh 


© 

© 

S 

o 

jd 


O 


(/) 

3 

O 


o 

_o 


o 

o 


3 

O 


Ph 




a 


Uh 


Ph 


a 






C/5 






C/5 


U 


a 


o 


O 


a 


O 

£ 

& 

0^ 


o 

Ph 


o 

< 


& 

Ph 


o 

PL. 


o 

< 

3 

eu 


Ph 




Ph 


Oh 



oo 

w 


w 




W 


W 




H 


(— 1 


a 


H 


H 


a 


U 


u 


u 


o 


u 


u 



( z rao/gu) 




(3/8u) 




SmpBoq 



uoijnijnaoucQ 


173 





















































Table A. 16 Summary statistics for cyfluthrin concentrations measured in soil (ng/g). 


* 

r~ 

CN 

n- 

CN 

o 

03 

s 

oo 

r—H 

CN 

N" 

n- 

SO 

CN 

o 

o 






r-H 

’B 

w~> 

CN 

CN 

CN 

CN 

Tf 

CN 

CN 

oo 

ico 

Os 

co 

•f 

SO 

"f 

oo 

,© 

wo 

wo 

wo 

OO 

l© 

+-> 

V 

V 

V 

V 

V 








wo 

wo 

wo 

wo 

VO 

o 

V 

V 

V 

V 

V 

wo 






J3 

in 

wo 

wo 

oo 

so 

tr> 

V 

V 

V 

V 

V 

CN 






3 

wo 

wo 

IT) 

I/O 

V© 

• r4 

s 

V 

V 

V 

V 

V 

Q 

O 

u 

u 

u 

o 

C/3 

o 

Z 

55 

z 

z 

z 

s 

u 

U 

u 

u 

o 

o 

z 

Z 

£ 

z 

z 

Q 

u 

o 

u 

u 

u 

O0 

55 

z 

z 

z 

z 

a 

o 

u 

u 

u 

o 

03 

z 

Z 

z 

z 

z 

S 






%Det 

CN 

oo 

r- 

oo 

o 



r-H 

CN 

r-H 

3 

os 

CO 

r- 

VO 

r- 


CN 

T—« 

CN 

r-H 

r-H 









© 


© 

© 

cu 

© 

U. 

<U 

H 

•a 


s 

03 

O 

s 

o 

c3 

o 

Vh 

o 

?o 

o 


?o 

O 

X 

o3 

Q 

X 

c3 

Q 

03 

Q 

T3 






O 

—X 


r-H 


r-H 

d 

b 


6 


o 

© 

on 


00 


cz> 

2 













u 


X 



>% 

& 


O 


U 

a 

Ph 


Oh 


U 

Ph 


Ph 


u 

c/} 

W 


W 



(—' 


H 




u 


U 




TJ 

© 

H-» 

3 


o 

*3 

o 


z 


#\ 

U 

55 



* 

Of 

oo 

s© 

Os 

o 


o 

o 

o 

o 

os 

d 

r-H 

r~~ 

SO 


co 


o 

wo 

if 

r-H 

3- 

2 

CN 

d 

d 


p 

d 


r-H 

Tf 

r~ 

r—H 

o 

CO 

o 

r-H 

OS 

.3 

s© 

oo 

WO 


r-~ 


O 

o 

o 

o 

oo 

oo 

os 

T—H 

o 

CN 

* 

CN 


SO 

n 

oo 

Os 

CN 

O 

d 

d 


O 

d 


so 

r-H 

o 

r-H 

CN 

OO 

oo 

-g 

'Cf 

_ 

3- 

Tf 

wo 


oo 

OS 

of 

oo 

o 

wo 

t" 

o 

CO 

wo 

c-~ 

o 


■^f 

CN 

oo 

3" 

o 

d 

d 

o 

d 

o 


CN 

CO 

CO 

so 

r-H 

W 




d 


d 






V 






V 







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m 

CO 

oo 

■^f 

wo 


o 

o 

wo 

so 

o 


o 

o 

r-H 

r-H 

o 


r-H 

r-H 

OS 

CO 

o 

in 

o 

o 

o 

o 

o 

d 

d 

o 

o 


V 

V 

r-H 

CO 

V 


d 

d 



V 








V 

V 










-S 

co 


CO 


wo 


o 

o 

o 

o 

o 

wo 

CN 

o 

o 

o 

o 

o 


r-H 

r-H 

r-H 

r-H 

o 

o 

o 

o 

o 

o 


V 

V 

V 

V 

r-H 

o 

o 

o 

o 

d 




V 


d 

d 

d 

d 

V 








V 

V 

V 

V 







3 

CO 

CO 

co 

CO 

wo 


o 

o 

o 

o 

o 

• h 

o 

o 

o 

o 

o 


r-H 

r-H 

r—H 

^H 

o 


o 

o 

o 

o 

o 


V 

V 

V 

V 

r-H 


o 

o 

o 

o 

d 



V 


d 

d 

d 

d 

V 








V 

V 

V 

V 







Q 

u 

U 

s© 

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U 


u 

o 

os 

r~- 

u 

oo 

O 

z 

z 

wo 

*—H 

Z 


z 

z 

cb 

cb 

Z 

5 

O 

o 

s© 

Os 

o 


o 

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o 

Z( 

O 

Z 

z 

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o 

z 


z 

z 

of 

r-H 

CN 

<N 

z 




d 

d 








Q 

u 

u 

o 

wo 

u 


u 

u 

CN 

co 

u 

oo 

z 

z 

r-H 

d 

d 

z 


z 

z 

OO 

CN 

CO 

z 

© 

o 

u 

so 


u 


u 

o 

Os 

os 

u 

03 

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2 

z 

z 

wo 

p 

d 

CO 

d 

z 


z 

z 

CN 

CO 

oo 

m 

z 

%Det 

oo 

CN 

■^f 

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o 


oo 

CN 

•'f 

3" 

o 

N- 

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r- 

r- 



■sf 

3" 

o 

t" 


3 


OS 

OS 

CO 

o 


_ 

Os 

OS 

m 

o 


CN 

*—H 

r-H 

CN 

CN 


CN 

r-H 

r-H 

CN 

CN 


i—H 


r-H 




’ 1 


r-H 





© 


© 




© 


© 


a, 

3 

O 

Vh 

© 

s 

o 

cd 

>> 

© 

a 

o 

c3 

>> 

AJ1 


© 

6 

o 

c3 

© 

a 

o 

Vh 

03 

O 

irv 

a 

X 

Q 

X 

cd 

Q 



X 

CC3 

Q 

X 

cd 

Q 





-H 


-*H 

(7) 


H 


>*H 

CO 

^3 


C/5 

-O 

3 


3 


3 

Q 


3 



3 

O 

•5 

Q 


Q 



Q 


Q 


Q 

Vh 


Vh 


© 


Vh 


Uh 


© 

0) 

o 


o 


C/5 


o 


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C/5 

2 

_o 


o 
• ■ < 


o 


_o 


£ 


3 

O 


Uh 


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X 


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C/3 




/ _^ 


C/1 


U 


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o 


u 


a 


o 


& 


O 


u 

< 


5c 


o 


U 

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s 

Oh 


cu 




Pl, 


Ph 



PL, 


Ph 




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C/3 

W 


w 


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w 


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H 


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H 


H 


a 


O 


O 


u 


U 


O 


u 



( z rao/3u) 




(g/3u) 




§UTpcoq 



UOIJBJ5U90UO3 


174 


NC, Not calculated 

















































Table A. 18 Summary statistics for TCPy concentrations measured in soil (ng/g). 


* 

_ 

o 

r~ 

o 

d 

1—< 

r- 

CN 

cn 

S 


1-H 


NO 



o 

NO 

o 

w-> 

o 

C"; 

OO 

co 

ON 



oo 

NO 

-a 

in 

in 

CN 

«n 

>n 

CN 

cn 

p 

cn 

r-~ 

T—H 

o 

CN 




CN 

O 

cn 

o 

<n 

o 

t-'' 

NO 

m 

o 

V 

o 

o 

-S 

CN 

CN 

m 

CN 

<n 

O 

O 

CN 

CN 

CN 

V 

V 

o 

o 

3 

<N 

CN 

CN 

CN 

S 

O 

o 

o 

o 

V 

V 

V 

V 

Q 

CN 

u 

in 

r- 

C/3 

CN 

£ 

CO 


O 

■it 


N" 

CO 

GM 

0.62 

NC 

0.82 

0.60 

Q 

ON 

u 

co 


C/3 


z 

in 





»—< 


C 

_ 

u 

ON 

>n 

cd 

<L> 

NO 

z 

ON 


s 

CO 


cn 


3 

Q 

w—4 

NO 

o 


t"- 


oo 

oo 

n° 

o x 





C3 

On 

co 

r-~ 

NO 


CN 

i—i 

CN 

1-^ 


y—* 






o 


CD 

a 

a 

j_ 

cd 

<D 

H 

cd 

o 

S 

o 

>> 

B 

o 

o 

Sn 

o 

a 

cd 

Q 

a 

cd 

Q 

T3 





O 

i 


,__ 


3 

o 


• r-H 

O 


03 

C/3 


C/3 


S 










U 


a 


> 

£ 


o 


"O 

2 

a 


a 


a 


a 


C/3 

w 


w 



H 


H 



O 


U 



T3 

4) 

3 

3 

O 

3 

o 

*-> 

o 

£ 

€\ 

U 

z 


60 

31 ) 

a 


o 

C/3 


'O 

<D 

O 

C/3 

cd 

<D 

s 

oo 

C 

o 
• ^ 
4-» 

cd 

H 

-*-> 

a 

<D 

O 

C 

o 

O 

1 

M 

Vh 

£ 

on 

O 

tt> 

4—» 

C/5 

c3 

s 

| 

13 

<73 

ON 


< 

<u 

F—< 

•s 

H 


Max 

162 

1.43 

95th 

2.07 

1.43 

-B 

co 


in 

p 

p 

C*~ 

o 

O 

3 

CN 

CN 

o 

o 

O 

>n 

V 

V 

3 

CN 

CN 

m 

O 

o 

CN 

V 

V 

3 

CN 

CN 

s 

O 

O 

V 

Q 

U 

o 

C/3 

Z 

Z 

o 



s 

o 

o 

o 

z 

z 

Q 

u 

o 

C/3 

z 

z 

C3 

u 

u 

cd 

<u 

z 

z 

s 




r-H 

oo 

Q 

o x 

"d" 

m 

s3 

m 

NO 


(N 

y—* 






CD 

a 

(D 


3 

O 

i-i 

s 

o 

ra 

O 

O 

a 

rt 

Q 

-o 



o 

i 


3 

o 


03 

C/3 


s 







a 


>N 

o 


"O 

2 

a 

a 


C/3 

w 



H 



O 



T3 

<u 

■*—* 
C3 

3 

3 

o 

-*-* 

o 

Z 

cn 

u 

z 


175 






































Total Available Surface Residue Loadings 


Table A.20 Summary statistics for chlorpyrifos in Total Available Residue (ng/cm 2 ). 

Max 

7.49 

3.64 

27.58 

4.29 

138.4 

ZVZ 

2.33 

o 

CN 

O 

1.22 

24.64 

1.90 

23.76 

9.83 

7.61 

5.54 

14.4 

229 

229 

o 

oo 

oo 

oo 

95th 

7.49 

1.51 

0.97 

0.67 

10.22 

3.12 

2.33 

0.19 

1.04 

10.85 

1.57 

6.57 

9.57 

5.40 

5.54 

r- 

ro 

179 

61.0 

o 

oo 

oo 

oo 

75 th 

<0.07 

1.15 

0.13 

0.13 

2.71 

0.72 

tT 

o 

o 

0.079 

0.57 

1.96 

0.61 

ZY\ 

61*3 

r- 

q 

t— H 

o 

y—4 

2.65 

25.2 

8.66 

1370 

50th 

<0.07 

<1.15 

0.02 

q 

o 

0.50 

0.39 

0.006 

0.046 

0.099 

0.82 

0.26 

0.35 


0.89 

1.26 

1.68 

ZV6 

2.82 

470 

25th 

<0.07 

<1.15 

<MDL 

^r 

o 

o 

o 

0.16 

0.16 

<MDL 

C" 

y—* 

o 

o 

0.02 

0.43 

0.02 

oo 

o 

0.34 

0.30 

0.83 

0.79 

5.00 

1.26 

270 

Min 

<0.07 

<1.15 

<MDL 

►J 

Q 

S 

V 

<MDL 

<MDL 

<MDL 

<MDL 

0.02 

0.07 

0.02 

0.031 

0.03 

0.025 

0.14 

0.63 

q 

0.14 

120 

GSD 

NC 


LL 

6.4 

12.5 

12.0 

17.0 

2.96 

4.91 

3.68 

5.24 

4.40 

4.17 

3.96 

3.81 

2.07 

4.16 

4.46 

3.71 

GM 

NC 

0.83 

0.027 

0.036 

rr 

o' 

0.21 

0.014 

0.037 

10 

0.95 

910 

0.52 

0.99 

0.62 

1.07 

1.64 

11.5 

3.58 

627 

SD 

NC 

0.41 

2.28 

0.53 

20.32 

r—H 

0.77 

0.057 

0.38 

4.30 

oo 

o 

4.84 

2.66 

1.59 

ZVZ 

2.57 

56.4 

39.0 

2793 

Mean 

NC 

1.04 

0.38 

oo 

i—H 

O 

4.87 

0.85 

0.32 

0.060 

Os 

<N 

O 

2.39 

0.41 

1.97 

ZVZ 

1.24 

1.89 

2.23 

31.6 

14.6 

1548 

%Det 

t~~ 

(N 

VO 

VO 

cn 

r- 

r~ 

oo 

oo 

r- 

t" 

VO 

95 

09 

o 
o 
»—< 

65 

o 

o 

r-H 

100 

100 

100 

100 

100 

100 

100 

c 

VO 

66 

oo 

VO 

o 

oo 

VO 

Os 

Os 

o 

cs 

20 

r- 

Os 

20 

VO 

6£ 

40 


oo 

<N 

■'t 

CN 

r~- 

vr> 

Ov 

Group 

Window Sill 

Floor 

Floor 

Desk/Table 

Floor (Screening) 

Floor 

Play Area 

All 

Living Area/Kitchen 
(Pre-application) 

Living Area/Kitchen 

Bedroom 

(Pre-application) 

Bedroom 

Cumulative 

Interval 

Bedroom 

Den 

Kitchen 

nv 

Kitchen 

Method 

Surface Wipe 

LWW 

Surface Wipe 

Surface Wipe 

Surface Wipe 

LWW 

Deposition 

Coupons 

Deposition 

Coupons 

Surface Wipe 

Study 

NHEXAS-AZ 

MNCPES 

ccc 

JAX 

CHAMACOS 

CPPAES 

Test House 


176 


NC, Not calculated 

LWW, Lioy-Weisel-Wainman sampler 




































Table A.21 Summary statistics for diazinon in Total Available Residue (ng/cm 2 ). 


■5 

»n 

ON 


CN 

V 


O 

X 


no 

</o 

cd 


co 

oo 


oo 

CN 

d 


On 

CN 

co 


co 

co 

ro 


co 


CO 

o- 


Vo 
On 
O 


CO 

On 

O 


oo 

O 

CN 


OO 

d 

CN 


NO 

OO 


NO 

t" 


•s 

NO 

r- 


NO 

CO 

V 


NO 

o 

d 


CN 

o 


CN 

NO 


CO 

d 


(N 

O 

o 


CO 

d 


•3 

o 

<o 


CN 

V 


>o 

CO 

V 


o 

o 


CN 

o 

o 


CN 

o 

o 

d 

V 


CN 

o 

o 

o 

V 


*o 

oo 

CO 


•3 

>o 

CN 


«o 

CO 

V 


CN 

o 

o 


CN 

o 

o 


CO 

o 


CN 

o 

o 

d 

V 


NO 

CN 


.s 


CN 

V 


NO 

CO 

V 


o 

o 

d 


o 

o 


CN 

o 

o 

d 

V 


CO 

d 

V 


Q 

CO 

o 


u 

z 


u 

z 


On 


NO 

d 


f- 

CN 


s 

o 


u 

z 


o 

z 


u 

z 


r- 

Tl- 


Q 

CO 


U 

Z 


p 

NO 


V 

z 


t" 

oo 

NO 


o 

Z 


NO 

CO 


U 

z 


NO 

o 

X 


On 

OO 


N- 

-o- 


NO 

OO 


NO 


OO 

NO 


On 


On 


& 

O 

Xi 

o 


<u 

H 

CO 

OJ 

Q 


OX) 

_c 

'2 

<u 

<D 

X 

O 

CO 


o 

E 


>N 

E 


a 

o 

. ts 

o £ 

£ CX 

* & 

I 

22 


"T3 

O 

■3 

o 


<D 

O, 


<D 

a, 


<u 

o 

— 

t- 

3 

co 


<u 

cx 


<u 

o 

.03 

M-l 

t- 

3 

CO 


&> 

o 

,c3 

x 

3 

CO 


o 

cx 


o 

o 

.3 

Xh 

l-l 

3 

CO 


>N 

*o 

3 

CO 


5 ! 

I 

C/D 

< 

x 

w 


u 

u 

u 


u 



* 

_ 

oo 

oo 

d- 



d 

s 

OO 

On 

NO 

CN 

t''; 

r—* 

CN 

OO 



ON 


•5 

On 

NO 

CN 

d" 

r- 

_ 

<o 

t'-; 

•d; 

CN 

CN 



On 

d 

d 

CO 

N- 

On 


•3 

oo 

NO 

o 

On 

On 

r-H 

NO 

o 

p 

d 

p 

°® 

CN 

O' 

d 

d 

r —4 

»—H 

d 

d 

s 

CN 

NO 

CN 



o 

o 

«o 

O 

d 

o 

o 

CN 

CN 

CN 

d 

p 

d 

d 



d 







V 






d- 

*o 

ON 

CO 

NO 

co 

>o 

CN 

o 

o 


T—1 

o 

NO 

o 

o 

d 

d 

o 

o 


d 

d 



d 

d 



V 



V 


g 

CN 

NO 

>o 

NO 

NO 

NO 


O 

o 

o 

o 

o 

o 

s 

p 

p 

o 

o 

o 

o 


d 

d 

d 

d 

d 

d 



V 

V 

V 

V 

V 

Q 

CO 

N- 

On 

CO 

CO 

oo 

CO 

NO 

od 

On 

oo 

cn 

NO 

a 




CN 

CN 


S 

CN 

NO 

co 

<o 

On 


<N 

*—H 

ON 

m 

O 


o 

O 

o 

d 

d 

d 



d 

d 





Q 

NO 

NO 

NO 


CN 

NO 

CO 

co 

d 

NO 

NO 

cd 

cn 


d 



r—C 


d 

3 


NO 

NO 

NO 

C'' 

r-H 

03 

<L> 

£ 


NO 

O’ 

NO 

NO 

CN 

d 


OO 

oo 


d 

%Det 

o 


r- 

oo 


NO 

NO 

d- 

oo 

C" 

NO 

oo 

c 

oo 

o 

NO 

On 

On 

o 


NO 

OO 

N" 



CN 


















00 




a, 

Vh 

CO 

<D 

<3 

22 

u 

W 

<U 

X 


3 

o 

.03 

<4h 

Uh 

o 

< 

1—1 

o 

Ut 

o 

O 

C/D 

_o 

>N 

3 

o 

CX 

3 


ex 

c^J 



CO 

»H 

o 


E 





O 







E 





C/D 


C/D 



o 


<u 






cx 


cx 



Oh 

■o 

o 

£ 


£ 



£ 

3 

<D 


0) 



o 

o 

O 


o 



o 

£ 

<+-< 


<4H 



f cd 

x: 


U 


u. 





3 

CO 


3 

CO 



o 

C/D 







oo 







O 

>N 

"O 

U 


X 



O 

c 

3 

U 


< 




co 

L> 





B 







u 


177 

















































Table A.23 Summary statistics for trans-permethrin in Total Available Residue (ng/cm 2 ). 


X 

VO 

On 

CO 

VO 

VO 

VO 


>< 

r- 

o 

oo 

r-H 

in 

o 

d 

S 

ON 

r-H 

(N 


VO 

CO 

CO 


C3 

*«— i 

oo 

oo 

cn 

d 



vd 

ON 

VO 





vd 

d 

^H 


CO 

d 

rS 

r- 

(N 

o 

VO 

VO 

cn 



3- 

vo 

m 


<n 

m 

in 


On 

d 

vd 

cn 

CN 


in 

d 

o 

cn 

d 

tT 

o 

on 

r-H 

O 

N" 

VO 

i-H 



On 



N- 

r-H 

CO 

d 











d 




V 











V 





t" 

r-H 


oo 

<n 

On 


-a 

VO 

VO 

VO 

3" 

vo 

m 


r-H 

d 

r-H 

O 


^r 

CO 

3 

cn 

d 


«n 

r~ 

o 

o 

o 

o 

o 

o 

O 

d 

o 

o 

o 

d 










d 

d 

d 


d 

V 










V 

V 

V 


V 


CO 

CN 

m 

3- 

»n 

CO 


-g 

VO 

vo 

vo 

VO 

vo 

m 


o 

O 

On 

cn 

o 

CN 



O 

o 

o 

o 

o 

o 


d 

d 

cn 

d 

d 

O 



o 

o 

o 

o 

o 

d 










o 

d 

d 

d 

d 

V 










V 

V 

V 

V 

V 

-s 

<n 

m 

VO 

fN 

CN 

3 



vo 

vo 

vo 

vo 

VO 

m 

»n 

CN 

o 

o 

CN 

r-H 

o 

r-H 


«n 

CN 

o 

o 

O 

o 

O 

o 

o 

o 

O 

d 

d 

d 


o 

o 

O 

o 

O 

d 


d 

d 







d 

d 

d 

d 

d 

V 


V 

V 







V 

V 

V 

V 

V 

g 

m 

>n 

>n 

>n 

>n 

CN 


g 

VO 

vo 

vo 

VO 

vo 

in 


o 

o 

o 

o 

o 

o 


• r4 

O 

o 

O 

o 

o 

o 


o 

o 

o 

o 

o 

o 


s 

O 

o 

o 

o 

o 

d 


d 

d 

d 

d 

d 

d 



d 

d 

d 

d 

d 

V 


V 

V 

V 

V 

V 

V 



V 

V 

V 

V 

V 









Q 

O 

U 

u 

U 

U 

O 




CO 


oo 



U 


o 

r-H 

r-H 


00 

£ 

Z 

z 

z 

z 

z 

oo 

oo 

Ov 

On 

3- 

On 

>n 


O 







O 



r-H 

CO 











r-H 

O 

oo 

3" 

3 

oo 



o 

u 

o 

u 

u 

u 

o 

CO 

o 

CN 

o 

2; 

3" 

d 

r-H 

O 

d 

(N 

a 

a 

z 

z 

z 

z 

z 

z 


d 

© 





o 















'St) 








Q 

r—H 

l"- 

3- 

On 

r-H 

r- 


Q 

u 

o 

u 

u 

u 

o 

C/3 



On 

3 



O 

oo 

z 

z 

z 

z 

z 

z 


d 

(N 

»—H 

CN 

3" 

o 

P 

T3 

• H 

CO 






















a 

m 

CO 

CN 

On 

VO 

cn 

<U 

e 

u 

u 

u 

u 

o 

u 

cd 

<D 

CN 

CN 

O 

cn 

o 

3 


cd 

0) 

z 

z 

z 

z 

z 

z 

S 

d 

CO 

»—H 

r-H 

CN 

d 

0) 

s 





















<u 

Q 

\0 

CN 

o 

ON 

oo 

On 

«n 



r-~ 

r-H 

o 

CO 

r-H 

m 

VO 

VO 

OO 

r~ 

OO 

On 

a 

> 

Q 

sP 



CN 

CO 

r ” H 


0 s 







< 

ON 














r-H 








3 

oo 

o 

VO 

On 

On 

O 

cd 

c 

oo 

o 

vo 

ON 

ON 

o 


VO 

oo 




(N 

o 


VO 

oo 




CN 


y ~^ 






H 

a 





























• H 











00 




c 




ou 






Jg 

•p3 


03 


"C 






c3 


cx 

u 

o 

X> 

03 

f-H 

4> 

<u 

t-4 

Ih 

o 

<u 

, 

p 

CX 

3 

Vh 

o 

X) 

03 

f-H 

c 

4> 

Uc 

tH 

o 

4) 


o 

Vh 

O 

e 

3a 

CO 

o 

00 

jj 

E 

>> 

a 


•s. 

O 

Wh 

a 

o 

•—H 

Px 

3a 

C/5 

o 

C/3 

E 

cd 



<u 

Q 

Ih 

o 


e 


o 

u 


4> 

Q 

Vh 

O 


E 





o 

u- 




<2 



JO 

E 











CO 















O 















• rH 









<o 


4> 



o 

4—* 

• rH 


4) 


4) 



4) 


cx 


a, 



cx 


CX 


CX 



CX 

~o 

o 

£ 


£ 



£ 

cd 

4—* 

T3 

O 

5 






•3 

4> 


4) 



4) 

CO 

3 

4> 


4) 



4) 

<u 

o 

.03 

<4H 


o 

.03 



o 

.03 

j_ 

>N 

c3 

4) 

s 

o 

f^ 3 

4h 


O 

5 



O 

.3 

‘C 


a 


3 



3 



3 


3 



3 


c/3 


oo 



OO 



00 


OO 



00 








p 














oo 

00 







oo 







o 








O 


U 


* 



U 

< 

CN 

”3 

U 





U 

< 

a 

U 






< 

B 

U 






oo 

U 


>—> 



^3 

4> 

oo 

u 


>—> 










X 

3 







K 







u 

c3 







U 








H 








T3 

42 

"a 

o 

"3 

o 

4-J 

o 

z 

U 

Z 


178 












































Transferable Surface Residue Loadings 





CD 

S3 

"w 

CD 

CD 

Jd 

Uh 

tZI 


J-i 

H 




x. 

>n 

o 

_H 


CN 

VO 

vo 

CN 

OV 

Ov 

vo 

m 

cd 


r-~ 

CN 


O 

OO 

r- 

CN 

O 

t" 

oo 



VO 

d 

d 

d 

o 

cd 

o 

CO 

o 


vd 

d 






d 




V 

o 



-s 


cn 

m 

Tf 

CN 


VO 

CN 

Ov 

cn 

vo 

m 

in 

ov 


co 

r—t 

t-H 

r- 

c—H 

o 

CN 

o 

vo 

oo 

r—H 

d 

d 

d 

d 

o 

d 

d 

CO 

d 

r—4 

vd 

d 



V 



d 




V 

d 



-S 

co 

CO 

CN 

<n 

Ov 

co 

VO 


OV 

N" 

CN 

r' 

m 

co 

co 

H—* 

N" 

o 

f-H 

O 

o 

o 

r- 

VO 


d 

O 

o 

O 

o 

O 

o 

o 

d 

o 

d 

o 


V 

V 

d 

d 

d 

d 

d 

d 

V 

o 


d 

.3 

co 

co 

vo 

t- 

VO 

co 

_ 

CN 

OV 

_ 

CO 

m 


co 

co 

vo 

o 

co 

o 

o 

o 

o 

CO 

(N 

'Cf 

m 

d 

V 

O 

V 

o 

o 

o 

d 

O 

O 

o 

d 

p 

d 

o 

d 

d 

V 

o 

d 

d 

O 

o 



d 


d 







d 

-s 

m 

co 

_< 

co 

m 


r- 


Ov 

N" 

_ 

CN 

in 

CN 

co 

co 

co 

o 

r—< 

o 

o 

o 

O 


*—H 

o 

O 

V 

d 

V 

O 

O 

o 

d 

o 

o 

o 

d 

o 

o 

o 

d 

d 

V 

O 

d 

d 

p 

d 



d 


d 


d 












V 






3 

co 

co 

r— 

r~ 


r-~ 



Ov 

<N 

CO 



m 

co 

o 

o 

o 

o 

o 

o 

o 

O 

o 

o 

s 

d 

V 

O 

V 

o 

p 

o 

o 

o 

o 

o 

o 

o 

o 

o 

o 

d 

V 

o 

o 

d 

V 

p 

d 


d 

d 

d 

d 

d 

d 






V 

V 

V 

V 

V 

V 





Q 

CJ 

cj 

vo 

oo 

CD 

oo 

o 

r*“H 

u 

CN 

CO 


CZI 

Z 

Z 


«/S 


oo 



z 

O 

C—H 

p 

O 











in 

in 

s 

CJ 

o 

co 

oo 

m 

co 

vrv 

VO 

o 

VO 

VO 

r- 

z 

Z 

vo 

o 

O 


CN 

CN 

Z 

CN 

CN 

o 

o 

o 

o 

o 

o 

o 

O 

O 


o 



o 

d 

d 

o 

p 

O 


d 


d 




d 



d 

d 

d 





Q 

CJ 

CJ 

m 

n- 

CO 

3- 

»—• 

Ov 

CJ 

"cr 

VO 

Ov 

CZI 

z 

z 

o 

d 

o 

d 

CN 

o 

oo 

d 

CN 

d 

OO 

d 

z 

to 

p 

O 

CN 

m 

p 






d 





d 


d 

pH 

NC 

NC 

CN 

co 

_ 

OV 

oo 

to 

u 

CN 

CN 

o 

<D 

O 

d 

o 

d 

p 

d 

d 

vo 

o 

CN 

d 

z 

vo 

o 

O 

CO 

p 








d 



d 


d 


oo 

lo 

Ov 

Ov 


vo 

CN 

>o 

o 

o 


o 

<U 

oo 

oo 

Ov 

oo 

VO 

oo 


o 

Ov 

o 

Q 









r—4 


r—< 

nP 

0 s 













3 

(N 

<N 

oo 

00 

OO 

T— H 

CO 

CO 

o 

r-i 

VO 

VO 


o 

o 

CN 

*-H 

1 —* 

CN 

T—< 


CN 


r ““‘ 



















Uh 



Uh 










(U 
"♦—» 


Uh 

-♦—* 




3 

3 




Q 

3 


o 

C 




4) 

4) 



<L> 

Q 

3 


o 

3 

4> 



.3 

-3 

Cl, 



O 

4) 


O 


Uh 

CJ 

o 

3 

o 

,cd 

Oh 

CJ 

g 

Uh 

U 

g 


o 

."ti 

• h-H 

2 


<+h 

Uh 

o 

C 

o 

<u 

3 

o 

< 

o 



a 

Uh 

3 

OO 

B 

o 

o 

-3 

Z 

s 

o 

O 

a 


Uh 

4) 

4> 




Z 

o 


a 

o 

•*-* 




Q 

Q 








5 






T3 

o 

C/5 

C/5 

<L> 


4) 

a, 

• »-h 

£ 


Ih 

u 

3 

<D 

Dh 


t-H 

3 

C^ 

C/5 

<u 

Uh 

<u 

Dh 

• hH 

C/5 

C/5 

<L> 

Uh 

tH 

JJ 

O 

£ 

£ 


o 


oi 

O 


oS 

Oh 

o 

o 

,3 

C*H 

l-H 

3 

czi 

Oh 

oS 

S 

oo 

U 


o 

.3 

0-H 

1 -. 

3 

CZI 


S3 

Oh 

o 

4-< 

Vh 

S5 

00 


s 

Oh 

OO 

U 

OO 

f-H 

o 

Uh 

D 

0 h 

£ 

B 

00 

W 

Oh 

u 


u 

& 

Oh 

Oh 



/-V 

X 

o 

Oh 

Oh 



czi 

O 

U 

< 

CZI 

53 

Ph 

Ph 

4) 

CO 

3 

O 

a 


CZl 

§ 


W 



w 




u 

<u 



r^i 


H 



H 



a 

H 





U 



u 



u 





”3 

<l) 

03 

3 

_o 

3 

CJ 

o 

z 

U 

Z 


179 



































Table A.26 Summary statistics for diazinon in Transferable Residue (ng/cm 2 ). 


* 

o 

00 



CD 

ID 


r-H 

CN 

Ov 

vo 

Os 

cd 

co 

VO 

Os 

OO 

OS 

O 

CN 


O 

CO 


oo 


l-H 

CN 

d 

d 

d 

d 

d 

d 

d 

CN 

Ov 

CD 










V 




£ 

•D 

cd 

r-H 


co 

r-H 

r_ 


CN 

Ov 

u 

u 

id 

ID 

r-H 

<D 

00 

Ov 

o 

CN 

r-H 

q 

CO 

z 


Os 

O 

r-H 

d 

d 

d 

d 

d 

d 

d 

CN 












V 





"T 

D" 

CD 

oo 

d- 

r-H 


<N 

CN 

F- 

u 

u 


d 

r-H 

o' 

o 

o 

o 

o 

CD 

O 

o 

o 

o 

o 

O 

o 

o 

o' 

r-H 

r—H 

z 

Z 


V 

V 

d 

d 

d 

o 

d 

d 

V 




-S 




<N 

m 

i-" 

t~~ 

_ 

CN 

oo 

oo 

CN 


r-H 

r-H 

o 

o 

o 

o 

o 

o 

o 


r-H 

- * 


d 

V 

O 

V 

o 

d 

o 

d 

o 

d 

o 

o 

o 

q_ 

q 

d 

d 

V 

C<D 

cn 

V 






d 

d 












V 

V 







d- 

N- 

t" 

i" 

D" 

i-" 

r~~ 


CN 

D" 


u 

<D 

CN 

r-H 


o 

o 

O 

o 

o 

o 

o 

CN 

z 

z 

O 

V 

d 

V 

o 

o 

o 

o 

o 

o 

o 

o 

o 

o 

o 

o 

d 

V 




d 

d 

d 

o 

d 

d 








V 

V 

V 

V 

V 

V 








r- 

r~ 

d - 

t" 

r- 

D" 

CN 

CN 

CN 

CN 

• rH 


T—H 

o 

o 

o 

o 

o 

O 

o 

• 

* 

• 


d 

V 

O 

V 

o 

o 

o 

o 

o 

o 

o 

o 

o 

o 

O 

o 

d 

V 

V 

V 

V 




d 

d 

d 

d 

d 

d 







V 

V 

V 

V 

V 

V 





Q 

U 

u 


OO 

CD 

U 

U 

r-H 

O 

ID 

u 

u 

00 

£ 

z 

oo 

oo 


Z 

z 


Z 

cn 

Z 

z 

O 








1—H 






u 

u 

CN 

CD 


o 

o 

r-H 

o 

*D 

u 

u 

O 

z 

z 

o 

o 

o 

o 

o 

o 

z 

z 

o 

o 

z 

VO 

z 

z 




d 

d 

d 



d 





Q 

u 

u 

Os 

^H 

CN 

u 

u 

m 

u 

r—H 

u 

o 

oo 

Z 

z 

o' 

CN 

O 

CN 

© 

z 

z 

o 

o 

z 

r—H 

Ov 

z 

z 

C3 

u 

o 

VO 

m 

ID 

o 

u 

T“H 

u 

Ov 

o 

u 

cd 

<D 

s 

z 

z 

n 

o 

v o 

o 

o 

z 

z 

o 

d 

z 

d 

r-H 

z 

z 



d 

o 

d 








■<-> 

ID 

Q 

oo 

oo 

oo 

_ 

r~ 

oo 

r-H 

D’ 

o 

ON 

F~ 

CO 



VO 

VO 

vo 

CD 

co 

«D 


OO 

vo 

cn 

NO 

o x 













c 

CN 

CN 

oo 

OO 

oo 

_ 

co 

CD 

o 

Ov 

CD 

CO 


o 

o 

<N 

r-H 

r-H 

CN 

r-H 

r-H 

CN 





















Vh 



J-. 










ID 



ID 









Vh 

+-> 


«H 

H-* 









o 



o 

W 





cd 

a. 

V-< 

<L> 

o 


o 

<D 

£ 

O 

D 


Vh 

Vh 

<D 


o 

1-1 

o 

_o 

f cd 

‘G 

Ph 

ID 

u 

a 

o 

Ph 

D 

CJ 

a 

a 

o 

All 

o 

a 

3 

< 

>\ 

o 

Uh 

SJ 

oo 

a 

o 

<D 

P=l 

X 

a 

o 

ID 

ffi 


Ph 

O 

U 





ffi 

o 

-4-* 


X 

o 

•*H 





Ph 





2 



s 









ID 



ID 








C/D 


.& 


<3 

&, 


«H 

<D 

C/D 

C/D 



T3 

O 

C/D 

<L> 

Vh 


£ 


3 



3 

C/D 

<D 

Uh 

C/D 

<U 

Wh 



•5 

CL, 


(D 


p4 

ID 


p< 

Ph 

Ph 



ID 

oo 


o 

f cd 

1 


pH 

o 


pH 

OO 

OO 



S 

U 



s 

Ph 

£ 


5 

Ph 

r-H 

U 

r-H 

O 






on 



(Z) 












/-N 



CD 





CZ) 


U 



X 



o 




Study 

w 

Ph 

u 

§ 


& 

(X 

Ph 

W 



o 

PL, 

Ph 

W 



u 

< 

DIYC 






H 



f-i 










U 



u 



u 





T3 

ID 

-4-» 

C3 

3 

O 

3 

o 

t 

o 

£ 

U 

Z 


Table A.27 Summary statistics for cA-permethrin in Transferable Residue (ng/cm 2 ). 

Max 

nfr 

oo 

d 

50.1 

1.13 

5.2 

oo 

r~; 

d 

0.29 

<0.2 

95th 

0.832 

50.1 

1.13 

0.19 

0.78 

0.29 

<0.2 

75th 

361 '0 

0.361 

0.139 

0.064 

0.006 

0.012 

<0.2 

50th 

0.0443 

0.0596 

0.0229 

OS 

o 

o 

d 

<0.0007 

D" 

O 

O 

d 

<0.2 

25th 

o 

q 

d 

0.0062 

0.0038 

<0.0007 

o 

o 

q 

d 

V 

D" 

O 

O 

q 

d 

V 

<0.2 

Min 

<0.0007 

<0.0007 

■ < cr 

o 

o 

q 

d 

V 

<0.0007 

<0.0007 

D" 

O 

O 

O 

o 

V 

CN 

d 

V 

GSD 

VO 

oo 

D - 

CN 

CD 

r-H 

CN 

NC 

9.3 

NC 

GM 

0.034 

D" 

D" 

q 

d 

0.020 

r-H 

q 

d 

NC 

D" 

O 

O 

d 

NC 

as 

0.263 

11.7 

0.319 

1.13 

NC 

OO 

o 

d 

NC 

Mean 

0.161 

3.05 

0.164 

0.28 

NC 

0.035 

NC 

%Det 

£6 

£8 

m 

oo 

c-~ 

ON 

CO 

69 

o 

a 

oo 

CN 

oo 

oo 

r-H 

CN 

CD 

r—H 

CD 

o 

CN 

Group 

Home Floor 

Kitchen Counter 

Home 

Home Floor 

Kitchen Counter 

Home 

All 

Method 

Surface Wipe 

PUF Roller 

Surface Wipe 

PUF Roller 

Cl8 Press 

Study 

CTEPP (NC) 

CTEPP (OH) 

CHAMACOS 


180 


NC, Not calculated 




















































Table A.28 Summary statistics for trans-permethrin in Transferable Residue (ng/cm 2 ). 


X 

r—H 

3- 

VO 

00 

Ov 

Ov 

CN 

G 

S 

o 


r—H 

r-H 

r- 

CN 

O 

r-H 

>0 

r—4 

co 

0 

O 

V 

3 

CO 

3- 

VO 

CN 

Ov 

Ov 

CN 


oo 

r-‘ 


O 

C~~ 

CN 

0 

Os 

d 

>0 

T—H 


0 

O 

V 

£ 

Ov 

CO 

c- 

l'- 

CO 

OO 

CN 

in 

r-H 

C" 

r-H 

O 

0 

O 


d 

co 

O 

O 

0 

O 

V 



0 



0 

O 


•P 

3- 

CO 

CN 

_ 

r-- 

<3 

CN 


O 

CN 

O 

O 

0 

O 


co 

O 

O 

O 

O 

O 

0 

0 

O 

O 

O 

V 






0 








V 



-g 

<o 

VO 

CO 

r- 

r— 


CN 

<o 

(N 

o 

O 

0 

0 

0 

O 


o 

O 

0 

0 

0 

O 

C-D 

V 

d 

O 

0 

0 

0 

O 





0 

0 

O 






V 

V 

V 


g 

t-~ 

r- 

3- 

r- 

r- 

G" 

(N 

• rH 

o 

0 

O 

0 

0 

0 



o 

0 

O 

0 

0 

0 

O 

V 


o 

0 

O 

O 

0 

0 


d 

0 

O 

0 

0 

0 



V 

V 

V 

V 

V 

V 


Q 

OO 

VO 

3- 

co 

u 

CN 

0 

00 

Ov 

CN 

r-H • 

r-H 

£ 

00 

£ 

O 








GM 


—4 

00 

1 —H 

0 

ro 

u 

CN 

o 

3" 

O 

r-H 

O 

O 

2 

0 

O 

2 


d 

O 

CO 

O 


0 


Q 

oo 

>0 

3- 

CN 

0 

00 

0 

oo 

VO 

CN 

co 

co 


2 

p 

2 


T—H 

0 

r-H 


O 



d 







3 


00 

00 

00 

0 

co 

0 

G 

CD 

V) 

3; 

'"I 

CN 

£ 

p 

2 

S 

d 

CO 

0 

O 


0 


%Det 

m 

co 

co 

_ 

OV 

OV 

0 

ov 

00 

00 

r- 

co 

VO 


3 

oo 

00 

00 

4 

co 

co 

0 


CN 


*— 4 

CN 

r-H 


CN 



u. 



*H 





3 



3 



D. 

V- 

O 

J3 

4-4 

3 

3 

O 

3 

»h 

O 

C 

3 

O 

a 


3 

Ph 

O 

a 

Ph 

u 

a 

’—' 

2 

3 

C5 

0 

3 

3 

0 

< 

O 

s 

o 

3 

.3 

a 

s 

0 

3 

-3 

a 



a 

O 

-4—* 


a 

O 





£ 



2 




<D 



3 




-3 

O 

cl, 

S 


"o 

34 

• H 

£ 


t-H 

_3 

'o 

co 

C/3 

<D 

W-. 

■5 

3 


pi 

3 


Pi 

Ph 

3 

s 

o 

& 

V- 


Ph 

D 

O 

.G 

<PH 


§ 

00 

0 


3 


Ph 

3 

00 


Ph 


00 













00 


U 



ffi 



0 

>v 

•3 

3 

5 

Ph 

Oh 



O 

Ph 

Ph 



u 

< 

oo 

W 



W 





H 



H 



a 


U 



U 



u 


4) 

4—» 

JS 

3 

JJ 

3 

o 

4-* 

o 

2 

U 

2 





<D 

3 

33 

•4-4 

C/3 

<U 

04 


<D 



C/3 

O 


<3 

4-> 

C/3 



<U 

I’ 1 * 
■8 


H 


X 

CO 


4—H 

OO 


3" 

CN 

cd 

r-H 

0 

3- 

r- 

0 

O 


s 

d 

0 

0 

O 

0 

d 

0 

0 

O 

O 

V 



d 



d 

d 




V 



V 

V 


•3 

<0 

r- 

_ 

_4 

t" 


CN 

10 

OV 

0 

0 

3" 

3- 

0 

0 

• 

d 

0 

0 

d 

O 

d 

0 

0 

0 

0 

CD 

V 



d 



d 

d 




V 



V 

V 


p 

r- 


VO 


r- 

3" 

CN 

«o 

0 

0 

r—H 

0 

0 

O 


0 

0 

• 

0 

0 

O 

O 


0 

0 


0 

0 

O 

V 


d 

d 


d 

d 

d 



V 

V 


V 

V 

V 


-g 

r- 

r~' 

0 

r- 

r- 

3 - 

CN 


0 

0 

r-H 

0 

0 

0 



0 

0 


0 

0 

0 


0 

0 


0 

0 

0 

V 


d 

d 


d 

d 

d 



V 

V 


V 

V 

V 


-3 


r- 

<N 

r~ 

r- 

3- 

CN 

GO 

0 

0 

O 

0 

0 

0 


0 

0 


0 

0 

0 

V 

CN 

0 

0 

O 

0 

0 

0 


d 

d 


d 

d 

d 



V 

V 


V 

V 

V 


3 

r- 

t" 

3" 

r- 

r- 

3- 

CN 


0 

0 

O 

0 

0 

O 



0 

0 

O 

0 

0 

O 

V 


0 

0 

O 

0 

0 

O 


d 

d 

d 

d 

d 

d 



V 

V 

V 

V 

V 

V 


Q 

O 

0 

3" 

O 

U 

O 

0 

00 

O 


2 

cri 

2 

2 

2 

2 


O 

O 

CO 

O 

U 

U 

0 

a 

2 

2 

O 

O 

2 

2 

2 

2 

Q 

U 

u 

O 

O 

u 

O 

u 

00 

2 

2 

d 

2 

2 

2 

2 

s 

u 

O 

r-H 

U 

U 

O 

u 

G 

<D 

2 

2 

r-H 

2 

2 

2 

2 

S 



O 





%Det 

r~~ 

0 

00 

0 

0 

0 

0 



r- 





3 

00 

00 

00 

—, 

m 

CO 

0 


CN 

r—H 

r-H 

<N 



CN 



U 



u, 





3 



3 




U< 

-*-* 


Jh 





0 

G 


0 

H 



a. 

_g 

G 

O 

3 


0 

3 


3 

Uh 

u 

a 

Ph 

u 

a 


O 

Ui 

3 

d 

0 

2 

G 

0 

< 

a 

S 

0 

3 

-3 

a 

a 

0 

3 

JS 

a 



a 

O 


a 

2 








Nd 




<D 



3 





3 , 


tH 

V 

3 

• »-H 


tH 

V 

CO 

33 

0 

? 


’o 



”o 

2 

B 

3 


Pi 

3 


Pi 

3 

3 

S 

3 

t" 1 

C*H 

k* 

3 


B 

Ph 

O 

£ 


B 

3 

00 

r—H 

O 


00 


00 











00 


U 



a 



O 

>4 

33 

2 

& 

Ph 

Ph 



0 

Ph 

3 



O 

< 

00 

W 



W 





H 



f- 1 



a 


U 



u 



u 




181 














































Table A. 30 Summary statistics for chlorpyrifos measured in solid food, presented as both intake (jug/day) and concentration (jUg/kg). 


* 

oo 

m 

co 

CN 

CN 

t—H 

o 

VCN 

m 

oo 

3" 

3" 

d 

3"' 


r— ; 

i/S 



CN 

ON 

cn 

oo 


T-H 









d 


d 



■S 

VO 

3" 

o 

CN 


3" 

rH 

in 

vo 

vo 

3" 

3" 

m 

v-H 

vo 

3" 

in 

>n 

CN 

CN 

oo 

r-H* 

m 

o' 

r—H 

Os 


d 

d 





d 


o 



.5 

OO 

oo 

m 

CN 

o 

1—H 

ON 

m 

On 

3" 

in 

o 

in 

cq 


r—H 

r—H 

r-i 

oo 

m 

CO 

cn 

CN 

r-^ 

r-i 

r- 

d 

o 

d 


V 

d 

d 

d 

d 

d 


V 

•5 

VO 

ro 

r-H 

t—H 

o 

CO 

On 

o 

ON 

3- 

oo 

o 

o 

CN 

Ov 

r~ 

r“^ 

r— i 

in 

t-H 




cn 


m 

O 




V 

d 

d 

d 

o 

o 

d 

V 



O 

d 








£ 

3" 

Ov 

in 

oo 

o 

ON 

oo 

oo 

oo 

oo 

m 

o 



CN 

CO 

3; 

r—J 

CN_ 

o 

o 

p 

p 

CN 


CN 

O 



d 

V 

d 

d 

d 

d 

d 

d 

V 



O 

d 




V 

V 

V 

V 



3 

CN 

N" 

3- 

CN 

o 

VO 

oo 

oo 

oo 

oo 

o 

o 

• rH 
2 

^H 

d 

CN 

O 

CN 

O 

T—H 

d 

r-H 

V 

CN 

d 

o 

d 

o 

d 

o 

d 

o 

d 

>n 

o 

V 


V 

d 

V 

d 

V 



V 

V 

V 

V 

V 

d 

Q 

On 

m 

C" 

o 

U 

co 

3" 

C" 

o 


CN 

u 

on 

CN 

cn 

CN 

co 

z 

CN 

cn 

CN 

rn 

CN 

3" 

z 

O 













GM 

3" 

On 

CO 

VO 

u 


o 

3" 

On 

>n 


u 

CN 

d 

r- 

o 

r~ 

p 

rq 

d 

z 

>q 

d 

CN 

d 

d 

d 

d 

m 

d 

z 



d 

d 










Q 

3" 

vo 

oo 

VO 

u 

CN 

oo 

m 


ON 

m 

u 

CO 

VO 

VO 

r-3 

r—H 

Z 

r-I 

t-H 

CN 

vq 


CN 

z 


d 

o' 

o 





d 

d 

o 



3 

CN 

o 

co 

co 

u 

On 

r- 

CO 

oo 

o 

CO 

u 

d 

3" 

CN 

r-H 

t-h 

z 

cq 

«n 

CN 

co 

CN 


z 

2 

d 

d 

d 



d 

d 

d 

d 

d 



%Det 

_ 

«n 

oo 

o 

<n 

oo 

l/N 

3- 

VO 

On 

o 

VO 

Ov 

t- 

C" 

o 

^■H 

oo 

vo 

in 

VO 

vo 

o 












r*H 


3 

VO 

ON 

in 

ON 

o 

vo 

ON 


m 

ON 

On 



On 

CN 

CN 


CN 

ON 

CN 

CN 

CN 

CN 


T-H 










r-H 









C/3 



<D 





O - 





c3 


as 

as 



£3 


1 

1 


<u 

1 

S 

o 

K 

S 

o 

ffi 

1 

,_H 

o 

B 

a 


3 

3 

< 

>4 

CN 

VI 


>> 

3 

Q 

1 

Q 





Is « 

^ as 


-*—* 

+n 

p 

as 

p 

as 

■4—* 


T3 

<L) 

• »-H 

.2 « 

• 2 es 

as 

• rH 

as 

as 

• rH 

as 

a 

as 

H-* 

03 

as 

as 

• H 

•s 

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Q £ 

Q £ 

Q 

5 

Q 

Q S 

Q S 

5 

Q 

0) 

cu 

a, a. 

a, a, 

a 

a, 

a 

a, 

Cm 

cx, 

a, 

cx 

& 

2 

3 

3 3 

3 3 

3 

3 

3 

3 

3 

3 

3 

3 

3 

Q 

Q Q 

Q Q 

Q 

Q 

Q 

Q Q 

Q Q 

Q 

Q 


C/D 

O 

X 


si 

C/!> 

U 



C/3 

o 

Study 

w 

Ph 

O 

5? 

0-i 

Oh 

W 

H 

u 

O 

l 

Oh 

Oh 

W 

H 

O 

JAX 

i 

Kfl 

< 

X 

w 

w 

O. 

u 

& 

Oh 

3h 

w 

H 

O 

O 

Ph 

Oh 

w 

H 

U 

JAX 

u 

< 

X 

u 


<L> 

Ph 

B 

c 3 

o 

a 

3 

Q 

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OS 

4—* 

3 

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Oh 

3 

Q 

IS 

<D 

Q 

o B 

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t! 

Q 

2* o 

Q Z 

Cm. r 
3 O 

Q Z 


(Xep/3r/) 

9^ui 


(8H/ St 0 

U0IJBJJU9DU03 


182 

































Table A.31 Summary statistics for diazinon measured in solid food, presented as both intake (/tg/day) and concentration (//g/kg). 


Max 

0.64 

1.3 

0.21 

- 

0.67 

O) 

r-H 

o 

CN 

C"; 

NO 

0.89 

0.72 

0.23 

1.01 

1.05 

p 

r-H 

95th 

cn 

T—H 

O 

no 

On 

O 

o 

co 

r- 

o 

d 

r—H 

r- 

NO 

d 

00 

CN 

CN 

d 

O’ 

d 

r-~ 

r-H 

d 

oo 

d 

o 

CN 

d 

p 

r-H 

NO 

o 

r-H 

o 

75th 

<0.019 

o 

o 

o 

<0.024 

m 

o 

»o 

CO 

d 

V 

t - 

d 

V 

CN 

d 

V 

oo 

o 

d 

V 

oo 

o 

o 

oo 

o 

d 

V 

OO 

o 

o 

V 

H 

CO 

d 

o 

oo 

o 

d 

V 

50th 

On 

r— i 

O 

O 

V 

T 3- 

CN 

O 

d 

V 

<0.024 

o 

co 

d 

ro 

d 

V 

d 

V 

CN 

d 

V 

oo 

o 

o 

V 

oo 

o 

d 

V 

oo 

o 

d 

V 

oo 

o 

d 

V 

r- 

r-H 

d 

N - 

O 

d 

V 

V 

25th 

<0.019 

CN 

o 

d 

V 

<0.024 

co 

CN 

d 

NO 

CO 

d 

V 

r- 

d 

V 

CN 

d 

V 

oo 

o 

d 

V 

oo 

o 

d 

V 

oo 

o 

d 

V 

oo 

o 

d 

V 

NO 

d 

o 

d 

V 

V 

Min 

<0.019 

<0.024 

<0.024 

NO 

ON 

O 

d 

NO 

CO 

d 

V 

d 

V 

CN 

d 

V 

oo 

o 

d 

V 

oo 

o 

d 

V 

oo 

p 

d 

V 

oo 

p 

d 

V 

CN 

r—H 

o 

O’ 

o 

d 

V 

V 

GSD 

o 

O 

2 

U 

£ 

o 

CN 

o 

Z 

U 

£ 

O 

Z 

O 

Z 

U 

Z 

u 

£ 

o 

z 

On 

o 

£ 

u 

£ 

GM 

o 

z 

O 

Z 

u 

Z 

co 

d 

V 

z 

o 

z 

o 

£ 

o 

Z 

u 

£ 

u 

£ 

U 

Z 

co 

CN 

d 

u 

£ 

u 

z 

SD 

u 

£ 

u 

£ 

u 

z 

On 

CN 

d 

u 

Z 

u 

£ 

u 

z 

u 

£ 

u 

z 

u 

2 

o 

NO 

CN 

d 

u 

2 

u 

z 

Mean 

u 

£ 

u 

z 

V 

z 

CN 

N" 

d 

u 

z 

u 

£ 

u 

£ 

u 

£ 

u 

z 

u 

£ 

u 

z 

On 

CN 

d 

u 

z 

o 

z 

%Det 

o 

CN 

(N 

m 

co 

CN 

o 

o 

r-H 


o 

NO 

CN 

CN 

NO 

CN 

NO 

H" 

CN 

o 

o 

H- 

N" 

CN 

a 

o 

00 

CN 

>0 

CN 

NO 

On 

o 

CN 

o 

r—< 

OO 

CN 

CN 

NO 

CN 

ON 

CN 

NO 

ON 

r~- 

Group 

<3 

3 

3 

3 

5 

c/3 

k- 

cO 

<D 

>> 

CN 

VI 

5 

Home 

Daycare 

Home 

Daycare 

5 

3 

5 

Method 

Dup Diet 

Dup Diet/ 
Dup Plate 

Dup Diet/ 
Dup Plate 

Dup Diet 

Dup Diet 

Dup Diet 

Dup Diet 

Dup Diet/ 
Dup Plate 

Dup Diet/ 
Dup Plate 

Dup Diet 

Dup Diet 

Dup Diet 

Study 

MNCPES 

CTEPP-NC 

CTEPP-OH 

DIYC 

3 
►—» 

NHEXAS-AZ 

MNCPES 

CTEPP (NC) 

CTEPP (OH) 

DIYC 


CHAMACOS 



(* 

9 

Bp/Sr/) 
>pnui 



(3^/gr/) 

U0IJBJJU99U03 


Dup Diet, Duplicate Diet; Dup Plate, Duplicate Plate 
NC, Not calculated 








































Table A.32 Summary statistics for c/s-permethrin measured in solid food, presented as both intake (/xg/day) and concentration (/ig/kg). 


X 

VO 

cn 

cn 

ON 


oo 

o 



cd 

! 

as 

»—< 


oo 

r-H 

VO 


1—c 

S 

CN 

rH 



CN 

m 



CN 

oo 

oo 

in 

VO 

CN 

oo 

CN 

m 


on 

SO 


r—H 

r-H 

>n 

oo 

CN 

1 

on 

d 










Ov 

m 

o 

3- 

On 

CN 

On 

00 

in 

m 

t" 

r—H 

CN 

ON 

r-H 

*n 

CN 

hH 

o 

cn 

p 

O 

O 

d 

d 

d 

d 

d 

o 


d 


o’ 





V 



V 









Os 

o 



00 

oo 

OO 

OO 

On 


1—H 

VO 

CN 

CN 

o 

o 

o 

o 

CN 


O 

o 

O 

o 

d 

d 

d 

d 

o 


O 

d 

O 

d 

V 

V 

V 

V 



V 


V 

V 



.5 

ON 

3- 

N" 

3- 

oo 

oo 

oo 

oo 

o 

in 

CN 

^H 

CN 

CN 

CN 

o 

o 

o 

o 

oo 

O 

o 

O 

O 

d 

d 

d 

d 

o 


O 

d 

d 

d 

V 

V 

V 

V 

d 


V 

V 

V 

V 




s 

On 

3- 

3" 


oo 

oo 

oo 

oo 

CN 


r-H 

CN 

CN 

CN 

o 

o 

o 

o 

O 


o 

o 

O 

o 

d 

d 

d 

o 

d 


d 

d 

d 

d 

V 

V 

V 

V 

V 


V 

V 

V 

V 



Q 

U 

cn 

U 

o 

O 

U 

U 

U 

On 

oo 

O 

55 

i n 

2 

Z 

£ 

£ 

z 

£ 

d 

s 

u 

o 

u 

u 

u 

u 

u 

u 

On 

o 

2 

d 

2 

z 

2 

£ 

z 

z 

r-H 

d 

Q 

u 


u 

u 

u 

u 

u 

u 

CN 

GO 

2 

»—H 

z 

z 

2 

z 

z 

2 

N- 

s 

u 


u 

u 

u 

u 

u 

o 

VO 

Cd 

<D 

2 

CN 

z 

z 

z 

Z 

z 

a 

»“H 

S 










*—* 
■D 

Q 

o 

O 

oo 

o 

VO 

m 

r-H 


OO 

m 

«n 

CO 

CN 

3- 

CN 

cn 

CN 

r- 

NO 

o x 










a 

o 

On 

*n 

o 

ON 

N - 

m 

On 

On 


o 

CN 

CN 

o 

CN 

CN 

CN 

CN 





r-H 


r-H 











<L> 


0) 


CX 

3 

O 

Vh 

All 

All 

All 

All 

o 

a 

o 

13 

o 

>N 

<D 

a 

o 

c3 

>% 

All 

o 





X 

Cd 

Q 

X 

cd 

Q 



x— > 

x— » 

x-> 

x—» 

■J3 

o 

£3 

o 


T3 

o 

• —H 

<u 

<u 

<o 

o 

13 

<U 

cd 

o 

| 

Q 

5 

Q 

Q 

Q ex 

Q S 

Q 

<D 

cx 

cx 

ex 

ex 

cx 

ex 

ex 

ex 

ex 

s 

3 

Q 

3 

Q 

3 

Q 

3 

Q 

3 3 

Q Q 

3 3 

Q Q 

3 

Q 




x 






MNCPES 

U 

C/) 

U 

X 


Study 

£ 

pin 

ex 

m 

H 

o 

o 

i 

ex 

Oh 

w 

H 

u 

w 

Oh 

u 

& 

ex 

ex 

w 

H 

U 

o 

Oh 

ex 

w 

H 

u 

JAX 


(Avp/8rl) 


(§5pgry) 



9>p}UI 

U0UBJJU93U03 



u 

* 

G3 


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C3 
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3a 

a, 

3 

Q 

of 

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CX 

cx 

3 

Q 


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Q 

Q 


ca 

o 


T3 
<u 

c5 

Q C3 
° 

■2 Z 
Q 2 

3 y 
Q 2 



X 

Tf 

in 

o 

ON 

o 

On 

OO 

N 

CN 


3 

s 

r-H 

SO 

(On 

1 < 

IN 

H- 

N” 

CN 

CN 

d 











o 

• H 

-S 

<n 

so 

CN 

m 

N 

O 

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CN 

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r-H 

d 

d 

CO 

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P 

CN 

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d 



d 






d 











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C J 
c* 



On 

On 

oo 

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oo 

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OO 

<n 

o 

o 

•n 

IN 

o 

d 

r-H 

d 

SO 

O 

o 

d 

>n 

d 

r-H 

d 

r-H 

d 

o 

d 

■rr 

d 

T3 


V 


o 

V 




V 


cd 

■S 



N" 

oo 

oo 

oo 

oo 

oo 

CN 


o 

«n 

o 

d 

<n 

p 

CN 

O 

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d 

o 

d 

o 

d 

o 

d 

o 

d 

CN 

d 



V 

d 

d 

V 

V 

V 

V 

V 


'£3) 




V 







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r-H 



oo 

oo 

oo 

oo 

oo 

N 


33 

m 

CN 

o 

CN 

CN 

o 

o 

o 

o 

o 

r-H 

a> 

d 

O 

O 

d 

d 

d 

d 

d 

d 


V 

d 

d 

V 

V 

V 

V 

V 


cd 



V 

V 





d 












.a 

_ 



oo 

oo 

oo 

oo 

oo 

CN 

-d 

o 

CN 

CN 

o 

o 

o 

o 

o 

O 

o 

s 

d 

O 

O 

d 

d 

d 

d 

d 

d 

xo 

c/3 

ce 


V 

d 

V 

d 

V 

V 

V 

V 

V 

V 

V 

T3 

Q 

U 

^H 

u 

U 

U 

u 

O 

O 

oo 

D 

d 

u 

C/3 

(U 

lH 

O . 

GO 

O 

Z 

so 

2 

2 

2 

2 

2 

2 

ON 

3 

u 

N 

U 

U 

O 

o 

O 

O 

r- 

HH 

#N 

T3 

O 

cS 

T3 

O 

2 ; 

oo 

p 

d 

2 

2 

2 

2 

2 

2 

CN 

O 

Q 

u 

p 

U 

U 

O 

u 

U 

O 

rn 

• rH 

CO 

2 

oo 

2 

2 

2 

2 

2 

2 

IN 

O 











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d 











• r-H 

T3 

D 

a 

U 

<n 

U 

U 

U 

U 

U 

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cd 

<u 

2 

r-H 

2 

2 

2 

2 

2 

2 

CN 

t-H 

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m 

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VO 

<n 

rH 


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d 

r-H 

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cn 



CN 

cn 

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NP 

o x 










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3 

r-H 

oo 

m 


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ON 

Ch 


o 

CN 

CN 

o 

CN 

CN 

CN 

CN 


H 


r-H 

r-H 

^H 

»-H 

r-H 


r-H 



s 











1 











<>3 











s 







d> 


<U 


<3 

& 





0> 

Daycar 

<u 



Xh 

cS 

3 

2 

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All 

All 

All 

HV 

a 

o 

X 

a 

o 

X 

O 

cd 

Q 

nv 

CO 











o 



■£3 <D 

£s <u 

N— * 

N. 

<D 

■£j 

o 

X—» 

• i-H 

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• r-H 

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O 

■S 

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• rH 

Q 

•2 « 
Q ex 

•2 « 
Q ex 

(U 

5 

•2 ^ 
Q ex 

<U 

• H 

Q 

C3 

<u 

Q 

ce 

<u 

ex 

cx ex 

CX CX 

cx 

cx 

CX 

cx 

cx 

cx 

4— • 

3 

D 

3 3 

3 3 

D 

3 

3 

3 

3 

3 

CO 


Q 

Q Q 

Q Q 

Q 

Q Q 

Q P 

Q 

c3 



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CS) 

a 


u 

U- 

H 


00 

m 

cn 

Study 

MNCPE! 

% 

Ph 

ex 

w 

H 

U 

o 

1 

ex 

ex 

u 

H 

U 

w 

ex 

U 

& 

ex 

ex 

W 

H 

O 

o 

ex 

ex 

W 

H 

U 

JAX 












„ 0X) 

0) 

2 ^ 

H 3 


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(S^ySr/) 






U0IJBJJU9DU03 



184 


Dup Diet, Duplicate Diet; Dup Plate, Duplicate Plate 
NC, Not calculated 





















































Table A.34 Summary statistics for TCPy measured in solid food, presented as both intake (fig/ day) and concentration (fig/kg). 


* 

>n 

oo 

oo 

00 

CO 

t-- 

CN 


<n 


r-H 

»— H 

CN 

CN 

r i 

■3 

•*t 

CO 

VO 

VO 

OO 

^H 

CN 

«n 

co 

CN 

oo 

SO 

«n 

OO 


On 






3 

oo 


oo 

«n 

CO 

>n 

H—H 

in 

r- 

r-H 

r-H 

CO 


CO 

CN 

(> 

3 

o 

CN 

r-H 


2.3 

2.9 

1.9 

in 

r*H 

3.2 

>n 


o 





-s 

^■H 

t—H 

*n 

CO 

0 

00 

^3* 

<n 


*0- 

r-H 

CN 

r-H 

ON 

CN 

CN 

© 

o 




O 

.s 

oo 

oo 

CN 

*n 

CO 

OO 

O 

S 

CO 

q 

CO 

o 

O 

CN 

0 

0 

co 

O 

CN 


o 

o 

V 


V 




V 






Q 

VO 

in 

VO 

CO 

r- 


ON 

on 

CN 

CN 

CN 

CN 

CN 

CN 

r-H 

O 







GM 

On 

O 

r-* 

00 

r- 

F- 

O 

On 

O 

o 

o 

CN 

CN 



N" 

as 

r- 

o 

OO 

CO 

VO 

0 

r- 

as 

. On 

CN 

co 

CN 

»n 

rn 


o 

O 






s 

"O' 

o 

r-H 

00 

VO 

00 

0 

CD 

»—H 

f—i 

rn 

rn 

CN 

CN 

>n 

s 








%Det 

On 

© 

oo 

0 

ON 

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0 

On 

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ON 

0 

On 

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0 






r—4 

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r- 

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On 


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CN 

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Q Oh 

^ 2 
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Q Oh 

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a, a, 

a, a. 

Oh 

cx 

a, 

Oh 

a. 


3 3 

3 3 

3 

3 

3 

3 

3> 

Q Q 

a q 

a a 

Q Q 

Q 








O 

s 

0 

5 



>> 

2 

I 

o 

i 

& 

O 


T3 

2 

C/3 

Oh 

Oh 

w 

H 

u 

Oh 

Oh 

w 

H 

U 

Oh 

Oh 

W 

H 

U 

Oh 

Oh 

W 

H 

U 

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(Aep/Sr/) 

95[B}IT[ 


(831 /Sri) 

UOUBJJU 93 U 03 


a> 

CO 

3 

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1—4 

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M ° 

Q Z 

3 u 

Q 2 



a 

o 


03 

H 


s 

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o 




I/O 

m 


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D 

H 


Max 

0.63 

0 

CN 

CN 

r-H 

•5 

00 

VO 

O 

«n 

«n 


On 

On 

0 


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•S 

0 

CO 

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in 

CN 

VO 

in 

c-' 

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£ 

CN 

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0 


m 

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0 

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NO 


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CN 

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O 


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.g 

O" 

CN 

CO 

S 

CN 

O 

r-H 

O 

0 


O 

V 

V 


V 


Q 

CN 

if 

CO 

on 

CN 

CN 

CN 

O 




S 

O’ 

NO 

O 

»-H 

CO 

co 

O 

O 

0 

O 

Q 



On 

on 


>n 

CN 


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0 

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3 

On 

CN 

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03 

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«n 


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O 

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r- 

00 

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Q 

£ 

On 

00 

00 

c 

CN 

0 

On 


m 


CN 




d> 

a, 


0 


3 

2 

All 

s 

0 

O 


X 

03 

Q 


<u 


0 

•o 

0 

3 

3 

Q Oh 

.g ,3 

Q 3 

0 

cx a, 

a 

a, 


3 3 

3 

3 


Q Q 

Q Q 


ffi 




>4 

O 

l 

O 

*a 

0h 



5 
c n 

Oh 

W 

H 

U 

MH 

Oh 

W 

H 

U 


(XBp/ 3 r/) 

( 8 ^ 3*0 


9 ^BJUI 

U 0 IJUJJU 99 U 03 


185 


Dup Diet, Duplicate Diet; Dup Plate, Duplicate Plate 
NC, Not calculated 














































Hand Loadings 

Table A.36 Summary statistics for chlorpyrifos hand loadings (ng/cm ). 


X 

r—H 

d" 

r~ 

NO 

oo 

oo 

NO 

d 



r- 

r-H 

NO 

r-H 

* 

s 

m 

d 

o 


d 






o 





,g 

c-» 

oo 

co 

r- 

NO 


r- 

>o 

On 

CN 

CN 

r- 

r-H 

r- 

r-H 

r- 

O 

d 

o 

d 

o 


d 




d 


d 



-g 

d* 

NO 

NO 

On 

r—H 

r- 

CN 

»o 

C" 

ON 

d 

co 

CN 

CN 

cn 

•d 

o 

o 

o 

O 

O 

d 


d 

d 

d 

d 

d 



-g 


o 

r- 

_ 

o 

On 

o 


o 

CN 

r-H 

r-H 

r—H 

* 

m 

O 

in 

d 

o 

O 

o 

O 


d 


V 

d 

d 

d 

d 



-g 

r- 

CN 

t-~ 

r~~ 


■d 

r-~ 

no 

CN 

o 

OO 

o 

o 

o 

r- 

00 

d 

o 

o 

o 

p 

d 

d 


V 


d 

d 

d 




d 

V 

V 

V 



.a 

r- 

r- 

r~ 


t" 

On 

NO 

o 

o 

o 

o 

o 

O 

r-H 

s 

d 

o 

p 

o 

p 

d 

O 


V 

d 

d 

d 

d 


d 


V 

V 

V 

V 



Q 

U 

On 

d" 

00 

p 

CN 

co 

on 

2 

co 

cn 

•d 

d- 

CO 

CO 

O 








s 

u 

O 

ro 

_ 

o 

NO 

On 

(N 

r—H 

r-H 

r— r 

• 


o 

z 

o 

O 

O 

o 


d 



d 

d 

d 

d 



Q 

u 


CN 

NO 

^H 

_ 

ON 

C/3 

z 

r—H 

o 

CN 

O 

r-H 

d 

<n 

CN 

d 




d 





ft 

CJ 

<n 

m 

oo 

NO 

oo 

CN 

cd 

<D 

s 

2 

<o 

o 

CN 

O 

d 

m 

o 

CN 

CO 

d 


d 

d 


d 



+-* 

<d 

On 

OO 

oo 

NO 

NO 

o 

o 

m 

r- 

NO 

NT, 

NO 

o 

o 

Q 

V® 

o x 






r-H 


a 

f- 

NO 

r—H 

r- 

ON 

oo 

d - 


On 

ON 

cd 

On 

CN 

m 

d- 




4> 


<13 



ft. 

ft 

o 

i_ 

<D 

C/3 

4> 

6 

o 

V-H 

cd 

o 

4> 

a 

o 

Vh 

cd 

£ 

<D 

C/3 

1 

Wipe 

O 

2 

X 

cd 

Q 

ffi 

cd 

Q 








>N 

C/3 

w 

U 

& 

ffi 

O 

'—i✓ 

C/3 

'O 

B 

PH 

y 

0h 

Oh 

Oh 

Oh 

< 

Oh 

C/3 


w 

w 

Oh 



H 

H 

U 



U 

O 




T3 

3 

3 

3 

o 

H-J 

o 

2 

U 

2 


CN 

§ 

"SB 

C/3 

00 

g 

• ^H 

cd 

o 


•G 

G 

O 

G 

•l-H 

*3 

t-H 

£ 

C/D 

o 

• r—H 
+-* 

C/D 

• r-H 
4-> 

cd 

+-> 

C/D 


X 

NO 


oo 

m 


r-H 

cd 

s 


r—H 

d 

rn 

On 

O 

On 

d 

CN 

d 





o 



^g 

•d 

r—H 

NO 

CO 

d 


NO 

ON 

oo 

NO 

r- 

d 

On 

CN 

p 

o 

p 

o 

d 

d 


d 

d 

d 

d 



-g 


d 

oo 


NO 

NO 

in 

r—H 

r—H 

NO 

r~ 

o 

o 

o 

o 

o 

o 

o 

o 


d 

d 

o 

o 

d 

d 




d 

d 

V 

V 

-g 

NO 

NO 

NO 

NO 

NO 

NO 


o 

NO 

o 

o 

o 

o 

in 

o 

d 

o 

o 

o 

d 

o 

d 

o 

d 

p 

d 


V 

d 

V 

V 

V 

V 

-g 

NO 

NO 

NO 

NO 

»o 

NO 

NO 

CN 

o 

o 

o 

o 

o 

o 

o 

o 

p 

o 

o 

o 


d 

d 

d 

d 

d 

d 


V 

V 

V 

V 

V 

V 

c 

NO 

NO 

NO 

NO 

NO 

NO 

• —H 

o 

o 

o 

o 

o 

o 

s 

o 

o 

o 

o 

o 

o 


d 

d 

d 

d 

d 

d 


V 

V 

V 

V 

V 

V 

Q 

O 

o 

U 

O 

NO 

m 

C/3 

Z 

cn 

2 

2 

CO 

CN 

O 







3 

u 

On 

O 

O 

On 

CN 

O 

z 

NO 

O 

O 

2 

2 

d 

On 

O 

d 



d 





Q 

o 

CN 

O 

O 

On 

m 

C/3 


CO 

o 

2 

2 

CN 

d 

o 



d 




d 

a 

o 

NO 

U 

u 

CN 

CN 

cd 

<D 

s 


r-H 

o 

d 

2 

2 

CO 

d 

d 

%Det 

NO 

NO 

_ 

_ 

o 

o 

m 

NO 

m 

m 

o 

o 





^H 


c 

NO 

r-H 


On 

NO 

m 


ON 

m 

ON 

CN 

r—H 

r-H 



<D 


<D 

& 


cx 

U3 

u* 

4) 

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o 

o 

Wh 

s 

o 

co 

o 

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s 

o 

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& 

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X) 

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C/3 

cd 

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irv 

o 


cd 

Q 

ffi 

cd 

Q 







Oh 



/ ^ s 





u 

X 



Study 

Oh 

Oh 

w 

o 

Oh 

Oh 

W 

PET 

DIYC 


H 

H 




U 

u 




TD 

3 

C3 

3 

jj 

3 

a 

H-> 

o 

2 

u 

£ 


(N 

I 

'ftb 

C/3 

00 

.5 

o 


,G 

G 

I 

W 


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Ph 

I 

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c2 

C/D 

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• r-H 
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cd 

C/D 

£ 

a 

1 

G 

00 

oo 

co 

< 

<u 

r—H 

3 

H 


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CN 

H 

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cd 

S 

NO 

CN 

CN 

- 


NO 


oo 

NO 

H 

in 

r-H 

rn 

oo 

NO 

On 


d 

d 

d 


NO 

NO 

NO 


«o 

c~- 

CN 

d 

d 

On 

O 

d 




d 


^g 

CN 

CO 

m 

NO 


NO 

r- 

co 

m 

in 

o 

p 

o 

o 


d 

d 

d 

d 

-g 

NO 

NO 

r- 

o 

NO 

CN 

CN 

ro 

r-H 

r-H 

O 

o 

o 

O 


d 

d 

d 

d 

g 

o 

NO 

NO 

NO 

• rH 

o 

o 

o 

o 

s 

o 

o 

o 

o 


d 

d 

d 

d 


V 

V 

V 

V 

Q 

t"~ 

ON 

ON 

NO 

C/3 

NO 

CO 

■^r 

NO 

O 





s 

r-H 


ON 

■Hf 


NO 

cn 

CO 

a 

o 

o 

o 

o 


d 

d 

d 

d 

Q 

NO 

oo 

o 

ON 

C/3 

NO - 

co 

rn 

CN 



d 

d 

d 

s 

CN 

r- 


NO 

cd 

On 

r—H 

r—H 

r-^ 

(D 





S 

O 

O 

O 

O 


NO 

N" 

oo 

ON 

Q 

OO 

On 

oo 

r- 

a 

NO 


r- 

ON 


ON 

m 

On 

CN 



4) 


4) 

Oh 

3 

o 

4) 

S 

c3 

o 

4) 

s 

S3 

o 

2 

O 


o 


a 

ffi 

cd 

p 

X 

cd 

Q 





O 

X 


£ 

o. 






3 

Oh 

Oh 

ft 

ft 

- 

C/D 

w 

w 


t- 

H 

h 

H 


u 

u 


186 

































































• 9 

Table A.39 Summary statistics for rra«s-permethrin hand loadings (ng/cm ). 


X 

t-~ 

r—H 

r-H 

NT) 

C3 

s 

NO 

oi 

CN 

r-H 

•5 

m 

NO 


co 

IT) 

r-I 

CN 


OO 

On 


O 

d 

d 

P 

00 

CN 

CN 

r~ 

in 

r- 

t-H 

r-H 

r- 

OO 

d 

d 

o 

o 

* 



d 

d 

•s 

On 

NO 

t"- 

OO 


N- 

co 

CN 

CN 

m 

o 

o 

O 

o 


d 

d 

d 

d 

•s 

uo 

o 

m 

f—H 

<n 

CN 

•—H 

CN 

r—H 

r—H 

o 

p 

o 

O 


d 

d 

d 

d 

q 

lO 

NT) 

LO 

NT) 

• *H 

o 

o 

o 

o 


o 

o 

o 

o 


d 

d 

d 

d 


V 

V 

V 

V 

Q 

On 

p 

On 

NO) 

C/3 

NO 

3 

3 

NO 

O 





S 

U~) 

NO 

CN 

O 

>n 


co 

co 

o 

o 

o 

p 

o 


d 

d 

d 

d 

Q 

OO 

OO 

N- 

co 

C/3 

NO 

co 

CO 

CO 



d 

d 

d 

C 

co 


CO 

NO 

Cd 

On 

»—< 

r-H 

r-H 

43 

s 

O 

d 

d 

d 

%Det 

NO 


OO 

On 

OO 

ON 

OO 

r- 

q 

NO 


r- 

ON 


ON 

co 

On 

CN 



43 


43 

cx 

q 

4) 

a 

H 

cd 

o 

43 

a 

cd 

o 

o 

o 

>4 

o 

>4 

O 

X 

03 

Q 

ffi 

cd 

Q 






o 

EC 

>> 

►- 

2 

O 

X) 

a 

Pu 

PU 

Pu 

0-, 

C/3 

w 

w 


H 

H 


U 

O 


T3 
1) 
H—4 

3 

O 

3 

o 

-*-» 

o 

2 

U 

2 





<u 

H 


X 


CN 

r- 

NO 

d 

1-H 

m 

NO 

cn 

s 

d 

o 

o 

o 



d 

d 

d 

•s 

d- 

ON 

m 

o 

«o 

On 

in 

CN 

m 

cn 

o 

O 

o 

o 


d 

d 

d 

d 


NO 

t'' 

On 

in 

NO 

r- 

CN 

r-H 

r-H 

1—H 

o 

o 

o 

o 


d 

d 

d 

d 

•s 

On 

o 

CN 

_ 


r—H 

f—H 

r-H 

r-H 

o 

wo 

O 

O 

O 

O 


d 

d 

d 

d 

•S 

CN 

NO 

On 

CN 

<o 

CN 

r-H 

NO 

r- 

NO 

o 

o 

o 

O 

d 

p 

o 

o 



d 

d 

d 

q 

_< 

CO 

CO 

cn 

• rH 


o 

o 

o 

s 

o 

o 

o 

d 

p 

d 

p 

d 


d 

V 

V 

V 

Q 

ON 

o 

p 

ON 

C/3 

r-H 

CN 

CN 

i—H 

a 





S 

OO 

o 

CN 

o 

r-H 


*—< 

*-H 

o 

p 

O 

O 

O 


d 

d 

d 

d 

n 

CN 

NO 

CN 

in 

C/3 

CN 

r-~ 

r-H 

r- 

O 

o 

o 

o 


d 

o 

d 

o 



d 


d 

q 

CO 

CN 

>n 

CN 

cd 

CN 

r—4 

»—H 

^H 

43 

O 

o 

O 

O 

s 

d 

d 

d 

d 

<u 

Q 

o 

q- 

OO 

o 

o 

On 

On 

On 

v9 

o x 





d 

On 

CN 

OO 

On 


ON 

co 

ON 

CN 



43 


43 

Oh 

<D 

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cd 

<D 

C3 

V-I 

cd 


d 

o 

c 

o 

o 

o 

>4 

o 

>4 

o 

EC 

cd 

Q 

X 

cd 

Q 





u 

X 

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£ 

o 

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a 

Oh 

Oh 

PLh 

Oh 

C/3 

w 

w 


H 

H 


O 

U 


T3 

0) 

3 

3 

o 

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o 

2 

C4 

o 

2 


"a 

4 

c 

N_' 

73 

00 

a 

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T3 

CO 

O 

T3 

£ 

cd 

^3 

Ph 

1 

V-i 

£ 

73 

o 
•»—* 
4-* 
73 


X 


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cd 

NO 

N" 

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o 

o 


d 

d 

3 

t" 


On 

o 

o 


d 

d 

3 

o 

■rr 

»-H 

CO 


o 

o 

r- 

o 

o 


d 

d 

3 

m 

o 

CO 

o 


o 

p 


d 

d 


V 

V 

3 

cn 

o 

CO 

o 

(N 

p 

p 


d 

d 


V 

V 

q 

CO 

cn 


o 

o 


o 

p 


d 

d 


V 

V 

Q 

u 

u 

C/3 

z 

2 

o 



s 

u 

U 

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q 

u 

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cd 

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z 

2 

s 




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CO 

£ 



q 

OO 

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CN 



43 

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43 

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q 

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o 

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a 

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cd 

Q 


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K 

>4 

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a 

Ph 

PL, 


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43 

-4—l 
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3 

o 

3 

o 

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o 

2 

r\ 

U 

2 


187 






















































Urinary Metabolite Concentrations 



X 

O 

NO 

o 



o 


C3 

CO 

N" 

o 

i—H 

CN 

CN 

NO 

S 








p 

NO 

CO 

NO 

CN 

r-H 

OO 

NO 


CN 

CN 

r “ H 

i-H 

CN 



ON 








P 

•0" 

CN 

''t 

oo 

«o 


o 

NO 

r—H 


o6 

t< 

r-H 


NO 









■5 

o 

CN 

Z'L 

5.3 

5.2 

9.8 

7.7 

2.8 

>0 








3 

t> 

p 

oo 

r-H 

NO 

<o 

cn 

IT) 

no 

tT 

co 

cn 

c< 

3 

r-H 

CN 








.3 

O 

N" 

o 

CN 

ON 

o 

N" 

S 

CN 

I—H 

r-H 

T“H 

CN 

r-H 

O 


V 

V 



V 

V 

Q 

CN 

cn 

-1 

p 

rl 

r-H 

CN 

CO 

CN 

CN 

CN 

r-H 

CN 

CN 

cn 

a 








s 

CO 

NO 

NO 

p 

-H 

N" 

p 

a 

Os 

NO 

NO 

3 

ON 

NO 

cn 

Q 

NO 

r- 

o 

NO 

N" 

C" 


C/3 

r< 

c< 


cn 

NO 

N 1 

NO 

s 

CN 

CN 

>o 

On 


O 

r~ 

cs 

<D 

1—1 

On 


«o 


OO 


S 








%Det 

o 

CN 

oo 

o 

o 

m 

o 

o 

ON 

ON 

o 

o 

On 

ON 

r-H 







G 


CO 

ON 

m 

On 


NO 


CN 

NO 

CN 

CN 


OO 

Tf 



CN 

r-H 

r-H 



CN 








'~ 4 

> 









C/3 






C/3 

CV 

c3 






c3 

p 

2 

<u 





r—( 

o 

Vi 

O 

?o 

CN 

VI 





3 

>N 

CN 

VI 

jo 

CO 

CO 

w 

U 

* 

ffi 

o 

1 


00 

w 

00 


< 

Pi 

Pi 

Pi 


<2 


3 

CO 

>< 

w 

U 

Pi 

W 

Pi 

W 

< 

>“3 

Pi 

Pi 

T 



H 

H 


O 

t^r 


§ 


O 

U 





<D 

G 

■§ 

G 

• iH 

T3 

<U 

Vi 

3 

C/3 

cd 

<D 

S 

< 

m 

Ph 

m 

Vi 

<2 

C/D 

O 


C/D 

cd 

H—» 

C/D 



m 

< 


<D 

I 

H 


Max 

m 

66 

254 

95th 

1.9 

66 

3.8 

75th 

690 

29 

oo 

p 

o 

50th 

0.32 

2.2 

0.34 

25th 

<0.20 

0.76 

0.13 

Min 

o 

CN 

O 

V 

0.39 

o 

© 

V 

GSD 

2.6 

7.5 

3.7 

GM 

0.38 

3.9 

0.36 

as 

3.0 

m 

m 

o 

Mean 

oo 

o 

19.6 

1.4 

%Det 

oo 

NO 

o 

o 

y—* 

79 

G 

126 

ON 

679 

Group 

All 

All 

C/3 

03 

a> 

Jo 

CN 

VI 

Study 

CTEPP-OH 

XVf 

NHANES 



X 

CN 

ON 


S 

3 

CN 

N" 

r-H 

-3 

NO 

5.5 

27 

3.0 

ON 




3 

NO 

1.5 

o 

r- 

o 

f" 



V 

3 

o 

CN 

NO 

it. 

C" 

o 

NO 

O 


V 

3 

NO 

ON 

CO 

4.4 

r> 

o 

CN 

o 


V 

Min 

CN 

CN 

o 

1.7 

r- 

o 

V 


V 



Q 

oo 

o 

U 

CO 

CN 

CN 


O 




GM 

0.75 

V L 

NC 

Q 

p 

ON 

U 

C/3 


NO 

Z 

9 

cn 

O 

u 

<u 

r-H 

ON 

z 

s 




%Det 

r- 

O 

NO 

r- 

o 

r-H 

r—H 

c 

o 


o 


m 

-N3- 

CN 




CN 








C^ 

Pu 



cd 

3 

r--4 

1 

<u 

O 

Vi 

o 

3 


CN 

VI 





Study 

PET 

DIYC 

1 


188 


NC, Not calculated 















































































APPENDIX B: Individual Study Details 










































National Human Exposure Assessment Survey in Arizona (NHEXAS-AZ) 

Collaborators: University of Arizona, Battelle Memorial Institute, and the Illinois Institute of 
Technology 

Study Design: 

• Type: Observational exposure measurement study with probability-based sample 

• Location: Each of the 15 counties in Arizona 

• Monitoring period: December 1995 to March 1997 

• Study population: 176 households (this report only includes data from 21 households in 
which the primary participants were children, ages 6-12) 

• Pesticide Use: Participants did not report use prior to the study 

Monitoring Protocol: 

• Indoor and Outdoor air: 3-day integrated samples; Personal air: 1-day sample 

• Surface Dust Loading: Modified Hoover “Port-a-Power” vacuum, center and comer of 
living room and bedroom; Window sill wipes 

• Soil: Yard surface soil composite sample 

• Beverages and solid food: 24-hour duplicate diet 

• Hand wipes: 4-mL IP A wipes of both hands 

• Urine: First morning void samples 

• Activities: Baseline and follow-up questionnaires, time-activity diary 

• Analytes (Pesticides): 

o Two pesticides of primary interest (and metabolites), namely chlorpyrifos (TCPy) 
and diazinon, and 14 secondary pesticides, including malathion (MDA) and 
carbaryl (1-naphthol) 

Key Outputs: 

• Occurrence, distributions, and determinants of total exposure to the general population 

• Geographic trends in multimedia exposure 

• Total exposures in minority and disadvantaged subsets of the population 


190 


Minnesota Children’s Pesticide Exposure Study (MNCPES) 

Collaborators: RTI, EOHSI, University of Minnesota, and Minnesota Department of Health 

Study Design: 

• Type: Observational exposure measurement study with probability-based sample 

• Location: Minneapolis/St. Paul (urban) and Goodhue and Rice counties (rural) 

• Monitoring period: Summer 1997 

• Study population: 102 children, ages 3-13 

• Pesticide Use: Households reporting a history of more frequent pesticide use were 
oversampled 

Monitoring Protocol: 

• Environmental samples: 

o Personal, indoor, and outdoor air: Integrated samples, days 1-7 (outdoor air for 
only 10% of urban homes) 

o Surface dust loading: Wipe and press, 2 indoor locations (main play area and 
family room), day 4 

o Soil: Surface soil grab sample, day 4 

o Beverages and solid food: Duplicate diet, 4-d composite, days 3-6 
o Tap water: Grab sample (10% urban homes), day 4 

• Biological/Personal samples: 

o Hand rinse, day 3 

o Urine: First morning void samples (88%) 3 samples per child, days 3, 5, and 7 

• Activities: 

o Baseline and follow-up questionnaires, time-activity diary 
o Videotape (4-h, about 20 homes) 

• Analytes (Pesticides and PAHs): 

o Pesticides: 4 Primary pesticides and metabolites, namely chlorpyrifos (TCPy), 
atrazine (atrazine mercapturate), malathion (malathion dicarboxylic acid), and 
diazinon, and 14 secondary pesticides 
o PAHs: 13 PAHs including fluoranthene, phenanthrene, and pyrene 

Key Outputs: 

• An "inverse" PK model to predict chlorpyrifos dose resulting both from specific pesticide 
applications and from average low-level exposures 

• Distributions and correlations in environmental and biological media (Adgate et al., 

2001; Clayton et al, 2003) 

• Evaluation of pathways of exposure 


191 


Children’s Total Exposure to Persistent Pesticides and Other Persistent Organic Pollutants 
Study (CTEPP) 

Collaborators: Battelle 

Study Design: 

• Type: Observational exposure measurement study with probability-based sample in 
homes and child care centers 

• Location: North Carolina (NC) and Ohio (OH) 

• Monitoring period: NC (July 2000 to March 2001); OH (April 2001 to November 2001) 

• Study population: 257 children, ages 18 months to five years, and their primary adult 
caregivers (NC = 130 children, 130 homes, 13 daycare centers; OH =127 children; 127 
homes, 16 daycare centers) 

• Pesticide use: Use during previous seven days were reported by a subset (n=38) of 
families in their homes 

Monitoring Protocol: 

• Sampling times: Samples collected over a 48-hr period at a home and/or daycare center: 

• Samples/data collected: Soil, outdoor air, indoor air, indoor floor dust, hand wipe, liquid 
food, solid food, urine 

• Supplemental information: 

o Recruitment survey, house/building characteristics survey, pre- and post monitoring 
questionnaires, activity and food diaries 

o In addition, 20% of the participants from OH were videotaped about 2 hours at their 
homes 

o Additional samples were collected if a pesticide was reported by the participant as 
having been applied indoors or outdoors at a home or daycare center within 7 days of 
previously scheduled field sampling or during the 48-hr monitoring period (hard floor 
surface wipe, food preparation surface wipe, and transferable residue) 

• Analytes of interest: Chlorpyrifos, diazinon, and cis-ltrans- permethrin 
Key Outputs: 

• Pesticide distributions in microenvironments where children spend time 

• Transfer of pesticides from microenvironmental media to child and factors that affect 
transfer 

• Evaluation of pathways of exposure 

• Evaluation of important factors the affect exposure 


192 


First National Environmental Health Survey of Child Care Centers (CCC) 

Collaborators: HUD, CPSC (US Department of Housing and Urban Development, US 
Consumer Product Safety Commission) 

Study Design: 

• Type: Observational study with probability-based sample of licensed child care centers 

• Location: Nationwide 

• Monitoring period: August 2001 to October 2001 

• Study population: 168 child care centers; no children or adults participated in the study 

• Pesticide use: Child care center directors reported on the professional or center staff 
applications during the previous 12 months 

Monitoring Protocol: 

• One time visit by field technicians to each child care center 

• Samples collected: Soil, surface wipes, transferable residues (surface press) 

• Analytes: Current-use pesticides - organophosphates and pyrethroids 

Key Outputs: 

• Data relating to pesticide use practices in child care centers across the US 

• Characterization of spatial distribution and magnitude of pesticide concentrations on 
surfaces in a sample of U.S. child care centers 


193 


Biological and Environmental Monitoring for Organophosphate and Pyrethroid Pesticide 
Exposures in Children Living in Jacksonville, Florida (JAX) 


Collaborators: CDC (Centers for Disease Control and Prevention), DCHD (Duval County 
Health Department) 

Study Design: 

• Type: Observational pilot exposure measurement study 

• Location: Jacksonville, Florida (Duval County) 

• Monitoring period: August to October 2001 

• Study population: Nine children 4-6 years of age 

• Pesticide use: Participants report recent pesticide use in the residences 
Monitoring Protocol: 

• Sampling times: One-time sample collection with 24-hour air samples 

• Samples collected: 

o Surface wipe 
o Indoor/outdoor air 
o Duplicate diet 
o Transferable residues 
o Cotton garments 
o Urine 

• Questionnaires: 

o Pesticide screening inventory 
o Time activity diary 

• Analytes: OP, pyrethroid pesticides, metabolites in urine 

Key Outputs: 

• The CDC component of the study determined the distribution of urinary metabolite levels 
of organophosphate and pyrethroid pesticides in a group of 4-6 year old children living in 
the greater Jacksonville, Florida area 

• The DCHD component of the study evaluated the use of screening wipes and pesticide 
inventories to identify homes with potentially elevated pesticide levels and to identify 
potential household sources for pesticides 

• The EPA nine-home study was performed to evaluate methods for aggregate exposure 
measurements, to determine whether environmental measures of pesticide exposure are 
correlated with biological samples for a sub-sample of homes using pesticide inventories 
and screening measurements, to evaluate if information collected from pesticide 
screening inventories about pesticides used in the home correlates with environmental 
measures found in the same homes, and to evaluate pathways of exposure and the 
important factors that affect exposure 


194 


Center for the Health Assessment of Mothers and Children of Salinas Quantitative 
Exposure Assessment Study (CHAMACOS) 

Collaborator: University of California at Berkeley 

Study Design: 

• Type: Observational pilot exposure measurement study 

• Location: Salinas, California 

• Monitoring period: June 2002 to October 2002 

• Study population: Twenty children ages 5 to 35 months old, 10 female, 10 male 

• Pesticide use: Incidental for farmworker children 

Monitoring Protocol: 

• Sampling times: 24-hour monitoring 

• Samples collected: 

o Indoor and outdoor air 
o House dust 

o Transferable residues from floors (surface wipes and press samples) 
o Transferable residues from toys (surface wipes) 
o Cotton union suits and socks 
o Urine 

• Activities 

o Videotaping 
o Time-activity diary 

• Analytes: acephate, azinphos methyl, bifenthrin, chlorpyrifos, chlorpyrifos oxon, cis- 
allethrin, trans-d\\Qt\mn, c/s-permethrin, frYzws-permethrin, cyfluthrin (I, II, III, IV), 
cypermethrin ( I, II, II, IV), dacthal, deltamethrin (I, II), diazinon, dimethoate, 
esfenvalerate, fonofos, iprodione, /cmMa-cyhalothrin, malathion, methidathion, naled, 
p,p’-DDE, p,p’-DDT, phosmet, resmethrin, sumithrin, tetramethrin (I, II), vincloziline 

Key Outputs: 

• Evaluation of methods for aggregate exposure measurements 

• Pesticide distributions in microenvironments where children spend time 

• Transfer of pesticides from microenvironmental media to child and factors that affect 
transfer 

• Evaluation of pathways of exposure and important factors that affect exposure 


195 


Children’s Pesticide Post-Application Exposure Study (CPPAES) 

Collaborator: EOHSI (Environmental and Occupational Health Sciences Institute) 

Study Design: 

• Type: Observational pilot exposure measurement study 

• Location: Urban New Jersey 

• Monitoring period: April 1999 to March 2001 

• Study population: 10 homes; children 2-5 years of age 

• Pesticide use: Crack and crevice application of chlorpyrifos was applied by a professional 
applicator in these homes 

Monitoring Protocol: 

• Sampling times: 1 day prior to application, 1, 2, 3, 5, 7, 9, and 11 days after application 

• Samples collected: 

o All sampling days: indoor air, deposition coupons, surface samples (LWW), toys, 
hand wipes, urine, air exchange rate, time activity diary 
o Additional day 2 samples - surface wipes, hand wipes, dermal wipes, cotton 
garments, videotaping 

• Analyte: Chlorpyrifos, TCPy in urine 
Key Output: 

• Pesticides distributions in microenvironments where children spend time 

• Transfer of pesticide from microenvironmental media to child and factors that affect 
transfer 

• Evaluation of pathways of exposure 

• Evaluation of important factors that affect exposure 


196 


The Distribution of Chlorpyrifos Following a Crack and Crevice Type Application in the 
US EPA Indoor Air Quality Research Test House (Test House) 

Collaborator: National Risk Management Research Laboratory 

Study Design: 

• Type: Field laboratory (Indoor Air Quality Research Test House) 

• Location: Cary, NC 

• Monitoring period: 3 weeks during November 2000 

• Study population: Single residential house; no occupants in the test house 

• Pesticide use: Chlorpyrifos, EC formulation, crack and crevice application in kitchen area 
(floor and cabinetry) 

Monitoring Protocol: 

• Sampling intervals: Pre, 1, 3, 7, 14 and 21 days post application 

• Sample types: 

o Application formulation concentration 
o Air (kitchen, den and master bedroom) 
o PUF-skin roller (den and kitchen) 
o Carpet sections (den and master bedroom) 

o 10-min Cl8 surface press (den carpet and kitchen vinyl floor), wipes (kitchen 
floor and counter) 

• Analyte: Chlorpyrifos 

Key Outputs: 

• Translocation and exposure pathways 

• Inputs to algorithms and SHEDS 

• Temporal and spatial variability over sampling period 


197 


A Pilot Study Examining Translocation Pathways Following a Granular Application of 
Diazinon to Residential Lawns (PET) 

Collaborators: None 

Study Design: 

• Preceded by a 1-home feasibility study 

• Type: Observational pilot exposure measurement study residential homes 

• Location: 50 mile radius of Durham, NC 

• Monitoring period: Ten days in Spring 2001 

• Study population: 6 homes, 1 child and care giver (typically mother) 

• Pesticide use: Homeowner applied diazinon, granular formulation, residential lawns (turf) 

Monitoring Protocol: 

• Sampling intervals: Pre, 1, 2, 4 and 8 days post application 

• Sample types: 

o Application formulation concentration 
o Air (living room and child’s bedroom) 
o PUF roller (lawn and indoor floor) 
o Soil 

o Entryway doormat 
o HVS3 

o Cotton gloves (technician and child) 
o Urine (adult and child) 
o Dog fur clippings 
o Dog paw wipes 
o Dog blood 
o Video graphy (15-min) 

Key Outputs: 

• Methods evaluation 

• Translocation and exposure pathways 

• Decay rates over sampling period 

• Inputs to algorithms and SHEDS 


198 


Dietary Intake of Young Children (DIYC) 
Collaborator: RTI 


Study Design: 

• Type: Observational pilot exposure measurement study 

• Location: Raleigh, NC area 

• Monitoring period: November 1999 to January 2000 

• Study population: 3 homes; children 1-3 years old 

• Pesticide use: Diazinon applications reported by homeowner - commercial crack and 
crevice (2 homes) or applied by resident (1 home) 

Monitoring Protocol: 

• Sampling times: Pre-application to 8 days post-application (7 visits total) 

• Samples collected: 

o Indoor and outdoor air 
o Surface wipes (isopropanol) 
o Entry wipe 
o PUF roller 
o Surface press 
o Hand wipes 
o Food press 
o Food samples 
o Urine 

• Analyte: Diazinon 

Key Outputs: 

• Evaluation of methods to measure excess dietary exposures that occur from activities by 
young children during eating 

• Children’s dietary intake model accurately represents total dietary exposures of children 

• Model predictions are closest to measured results with the highest measured 
environmental diazinon concentrations 

• Refinements for transfer and activity parameters within model are needed 

• Categories of transfers and activities for highly exposed vs. less exposed are needed 


199 


Characterizing Pesticide Residue Transfer Efficiencies (Transfer) 

Collaborator: Battelle 
Study Design: 

• Type: Controlled laboratory study 

• Objective: Evaluate parameters that affect residue transfer from surface-to-skin, skin-to¬ 
other objects, skin-to-mouth, and object-to-mouth 

• Monitoring period: not applicable 

• Study population: not applicable 

• Pesticide use: Nontoxic fluorescent tracers used as surrogates for pesticides 

Monitoring Protocol: 

• Conduct study using nontoxic fluorescent tracers as a surrogate for pesticide residues 

• Apply fluorescent tracer as a residue at levels typical of residential pesticide applications 
to surfaces of interest 

• Conduct controlled transfer experiments varying parameters in a systematic fashion 

• Hand Contact Trials 

o Systematically varied six parameters 
o Repetitive contacts with contaminated surface 

• Transfer off skin 

o Hand to clean surface 
o Hand to washing solution 
o Hand to mouth 

• Mouthing Trials 

o Varied 5 parameters 

o Simulated mouthing using saliva moistened PUF 

o Measured mass of tracer transferred and estimated contact surface area using 
video imaging techniques 

• Conduct laboratory evaluations to relate transfer of tracer to transfer of pesticides 
Key Outputs: 

• Transfer efficiency data 

• Information on type of microactivity data needed to estimate dermal exposure 

• Inputs for multipathway exposure models 


200 


Feasibility of Macroactivity Approach to Assess Dermal Exposure (Daycare) 

Collaborator: RTI 
Study Design: 

• Type: Observational pilot exposure measurement study 

• Location: North Carolina 

• Monitoring period: Three occasions, twice per occasion 

• Study population: Infants and toddlers at daycare centers 

• Pesticide use: Professional crack and crevice applications as contracted by the daycare • 
center 

Monitoring Protocol: 

• Identify up to 9 daycare centers with previously established contracts for routine monthly 
pesticide applications 

• In each daycare, conduct screening sampling to evaluate the distribution of transferable 
pesticide residue on floor surfaces in the area where children spend the most time 

• Select one daycare for intensive measurements 

• Children from different age groups volunteered to wear full-body cotton bodysuits for 
short time periods 

• Conduct surface sampling and videotaping of activities simultaneously with dermal 
loading sampling 

• Calculate dermal transfer coefficients 

Key Outputs: 

• Pesticide distributions in nine daycare centers 

• Verified protocol for collecting aggregate surface measurement 

• Verified protocol for collecting transfer coefficients 

• Dermal transfer coefficients developed with children (to evaluate default assumptions 
used in OPP’s SOPs) 


201 


Food Transfer Studies, also known as Press Evaluation Studies (Food) 


Collaborator: RTI 

Study Design: 

• Type: Controlled laboratory study 

• Location: NERL Cincinnati 

• Study period: Not applicable 

• Study population: Not applicable 

• Pesticide use: Organophosphate, pyrethroid, and pyrazole insecticides on various 
household surfaces 

Monitoring Protocol: 

• Surfaces: 

o Surface Treatment: A customized spray chamber was used to spray Pesticide 
Spray Solution (PSS) onto the ceramic tiles 
o Surface Drying: Following spraying, each ceramic tile was transferred to a glove 
box where it was air dried for an hour at constant temperature and humidity 
o Surface Wipes: Pesticide transfer to foods were compared to the pesticides 
removed using surface wipes (isopropanol moistened gauze pads), which were 
wiped across the ceramic tile in both the horizontal and vertical direction 

• Food Items: 

o Moisture Content: Moisture (%) content measured with a Denver Instrument IR- 
30 moisture meter 

o Fat Content: Fate (%) content determined from each food’s Nutrition Facts label; 

% fat = [total fat (g) / food serving size (g)] *100 
o Food Items: Pesticide transfer efficiencies were measured for three different 
foods, with standardized surface contact area; the foods were Fruit Roll-Ups 
Blastin' Berry Hot Colors® (Betty Crocker®), thinly sliced bologna (made with 
chicken & pork), and Red Delicious apple slices 

• Transfer Efficiency (TE): TE is defined as the amount of pesticide recovered from the 
food item divided by the pesticide concentration or loading level 

• Analytes: Malathion, Chlorpyrifos, Fipronil, Permethrin, Cyfluthrin, Cypermethrin, 
Deltamethrin 

Key Outputs: 

• Determine the extent of pesticide transfer from household surfaces to foods 

• Evaluate factors that have been identified as important, including surface type, duration 
of contact, surface loading, and contact pressure (applied force or weight per area) 

• Compared surface wipes using cotton gauze pads with the pesticide transfer to the foods 


202 







4>EPA 

United States 
Environmental Protection 
Agency 


PRESORTED STANDARD 
POSTAGE & FEES PAID 
EPA 

PERMIT No. G-35 


Office of Research and 
Development (8101R) 
Washington, DC 20460 

Official Business 
Penalty for Private Use 
$300 

EPA/600/R-07/013 
March 2007 
www.epa.gov 





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